mirror of
https://github.com/DOI-DO/j40-cejst-2.git
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Tile-baking columns with floating rounds completed (#491)
* Tile-baking columns with floating rounds completed * completed * correction on github workflow * tiles folder no longer needed * addressed comments * updating requirements.txt * poetry lock update * adding xlswriter * final poetrylock * updated requirements.txt * checkpoint * removed matplotlib * ignoring pylint too many statements * reinstated too many statements * converting data sync to generate score GHA UI-driven
This commit is contained in:
Jorge Escobar
GitHub
parent
176cb71d9a
commit
3d8dbb293c
8 changed files with 311 additions and 209 deletions
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@ -1,11 +1,11 @@
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name: Deploy Data
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name: Generate Score
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on:
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push:
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paths:
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- 'data/data-pipeline/*'
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pull_request:
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paths:
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- 'data/data-pipeline/*'
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workflow_dispatch:
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inputs:
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confirm-action:
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description: This will rebuild the data sources and regenerate the score, are you sure you want to proceed? (Y/n)
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default: n
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required: true
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jobs:
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deploy_data:
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@ -49,7 +49,9 @@ jobs:
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aws-region: us-east-1
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- name: Deploy to Geoplatform AWS
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run: |
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aws s3 sync ./data_pipeline/data/ s3://justice40-data/data-pipeline/data --delete
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aws s3 sync ./data_pipeline/data/dataset/ s3://justice40-data/data-pipeline/data/dataset --delete
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aws s3 sync ./data_pipeline/data/score/csv/ s3://justice40-data/data-pipeline/data/score/csv --delete
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aws s3 sync ./data_pipeline/data/score/downloadable/ s3://justice40-data/data-pipeline/data/score/downloadable --delete
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- name: Update PR with Comment about deployment
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uses: mshick/add-pr-comment@v1
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with:
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@ -57,4 +59,4 @@ jobs:
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Data Synced! Find it here: s3://justice40-data/data-pipeline/data/
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repo-token: ${{ secrets.GITHUB_TOKEN }}
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repo-token-user-login: 'github-actions[bot]' # The user.login for temporary GitHub tokens
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allow-repeats: false # This is the default
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allow-repeats: false # This is the default
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@ -193,6 +193,7 @@ If you want to run tile generation, please install TippeCanoe [following these i
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- Start a terminal
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- Change to the package directory (i.e. `cd data/data-pipeline/data_pipeline`)
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- Then run `poetry run generate_tiles`
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- If you have S3 keys, you can sync to the dev repo by doing `aws s3 sync ./data_pipeline/data/score/tiles/ s3://justice40-data/data-pipeline/data/score/tiles --delete`
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### Serve the map locally
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@ -27,10 +27,10 @@ class ScoreETL(ExtractTransformLoad):
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self.UNEMPLOYED_FIELD_NAME = "Unemployed civilians (percent)"
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self.LINGUISTIC_ISOLATION_FIELD_NAME = "Linguistic isolation (percent)"
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self.HOUSING_BURDEN_FIELD_NAME = "Housing burden (percent)"
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self.POVERTY_FIELD_NAME = "Poverty (Less than 200% of federal poverty line)"
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self.HIGH_SCHOOL_FIELD_NAME = (
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"Percent individuals age 25 or over with less than high school degree"
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self.POVERTY_FIELD_NAME = (
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"Poverty (Less than 200% of federal poverty line)"
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)
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self.HIGH_SCHOOL_FIELD_NAME = "Percent individuals age 25 or over with less than high school degree"
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self.MEDIAN_INCOME_AS_PERCENT_OF_STATE_FIELD_NAME = (
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"Median household income (% of state median household income)"
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)
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@ -51,86 +51,14 @@ class ScoreETL(ExtractTransformLoad):
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self.housing_and_transportation_df: pd.DataFrame
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self.hud_housing_df: pd.DataFrame
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def extract(self) -> None:
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# EJSCreen csv Load
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ejscreen_csv = self.DATA_PATH / "dataset" / "ejscreen_2019" / "usa.csv"
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self.ejscreen_df = pd.read_csv(
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ejscreen_csv, dtype={"ID": "string"}, low_memory=False
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)
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self.ejscreen_df.rename(columns={"ID": self.GEOID_FIELD_NAME}, inplace=True)
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# Load census data
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census_csv = self.DATA_PATH / "dataset" / "census_acs_2019" / "usa.csv"
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self.census_df = pd.read_csv(
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census_csv,
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dtype={self.GEOID_FIELD_NAME: "string"},
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low_memory=False,
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)
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# Load housing and transportation data
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housing_and_transportation_index_csv = (
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self.DATA_PATH / "dataset" / "housing_and_transportation_index" / "usa.csv"
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)
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self.housing_and_transportation_df = pd.read_csv(
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housing_and_transportation_index_csv,
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dtype={self.GEOID_FIELD_NAME: "string"},
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low_memory=False,
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)
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# Load HUD housing data
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hud_housing_csv = self.DATA_PATH / "dataset" / "hud_housing" / "usa.csv"
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self.hud_housing_df = pd.read_csv(
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hud_housing_csv,
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dtype={self.GEOID_TRACT_FIELD_NAME: "string"},
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low_memory=False,
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)
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def transform(self) -> None:
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logger.info("Transforming Score Data")
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# Join all the data sources that use census block groups
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census_block_group_dfs = [
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self.ejscreen_df,
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self.census_df,
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self.housing_and_transportation_df,
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]
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census_block_group_df = functools.reduce(
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lambda left, right: pd.merge(
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left=left, right=right, on=self.GEOID_FIELD_NAME, how="outer"
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),
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census_block_group_dfs,
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)
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# Sanity check the join.
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if len(census_block_group_df[self.GEOID_FIELD_NAME].str.len().unique()) != 1:
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raise ValueError(
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f"One of the input CSVs uses {self.GEOID_FIELD_NAME} with a different length."
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)
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# Join all the data sources that use census tracts
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# TODO: when there's more than one data source using census tract, reduce/merge them here.
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census_tract_df = self.hud_housing_df
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# Calculate the tract for the CBG data.
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census_block_group_df[self.GEOID_TRACT_FIELD_NAME] = census_block_group_df[
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self.GEOID_FIELD_NAME
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].str[0:11]
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self.df = census_block_group_df.merge(
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census_tract_df, on=self.GEOID_TRACT_FIELD_NAME
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)
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if len(census_block_group_df) > 220333:
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raise ValueError("Too many rows in the join.")
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def data_sets(self) -> list:
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# Define a named tuple that will be used for each data set input.
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DataSet = collections.namedtuple(
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typename="DataSet",
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field_names=["input_field", "renamed_field", "bucket"],
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)
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data_sets = [
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return [
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# The following data sets have `bucket=None`, because it's not used in the bucket based score ("Score C").
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DataSet(
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input_field=self.GEOID_FIELD_NAME,
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@ -251,9 +179,94 @@ class ScoreETL(ExtractTransformLoad):
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),
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]
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def extract(self) -> None:
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# EJSCreen csv Load
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ejscreen_csv = self.DATA_PATH / "dataset" / "ejscreen_2019" / "usa.csv"
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self.ejscreen_df = pd.read_csv(
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ejscreen_csv, dtype={"ID": "string"}, low_memory=False
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)
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self.ejscreen_df.rename(
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columns={"ID": self.GEOID_FIELD_NAME}, inplace=True
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)
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# Load census data
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census_csv = self.DATA_PATH / "dataset" / "census_acs_2019" / "usa.csv"
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self.census_df = pd.read_csv(
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census_csv,
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dtype={self.GEOID_FIELD_NAME: "string"},
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low_memory=False,
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)
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# Load housing and transportation data
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housing_and_transportation_index_csv = (
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self.DATA_PATH
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/ "dataset"
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/ "housing_and_transportation_index"
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/ "usa.csv"
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)
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self.housing_and_transportation_df = pd.read_csv(
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housing_and_transportation_index_csv,
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dtype={self.GEOID_FIELD_NAME: "string"},
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low_memory=False,
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)
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# Load HUD housing data
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hud_housing_csv = self.DATA_PATH / "dataset" / "hud_housing" / "usa.csv"
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self.hud_housing_df = pd.read_csv(
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hud_housing_csv,
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dtype={self.GEOID_TRACT_FIELD_NAME: "string"},
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low_memory=False,
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)
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def transform(self) -> None:
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logger.info("Transforming Score Data")
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# Join all the data sources that use census block groups
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census_block_group_dfs = [
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self.ejscreen_df,
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self.census_df,
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self.housing_and_transportation_df,
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]
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census_block_group_df = functools.reduce(
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lambda left, right: pd.merge(
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left=left, right=right, on=self.GEOID_FIELD_NAME, how="outer"
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),
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census_block_group_dfs,
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)
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# Sanity check the join.
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if (
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len(census_block_group_df[self.GEOID_FIELD_NAME].str.len().unique())
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!= 1
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):
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raise ValueError(
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f"One of the input CSVs uses {self.GEOID_FIELD_NAME} with a different length."
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)
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# Join all the data sources that use census tracts
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# TODO: when there's more than one data source using census tract, reduce/merge them here.
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census_tract_df = self.hud_housing_df
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# Calculate the tract for the CBG data.
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census_block_group_df[
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self.GEOID_TRACT_FIELD_NAME
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] = census_block_group_df[self.GEOID_FIELD_NAME].str[0:11]
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self.df = census_block_group_df.merge(
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census_tract_df, on=self.GEOID_TRACT_FIELD_NAME
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)
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if len(census_block_group_df) > 220333:
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raise ValueError("Too many rows in the join.")
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# get data sets list
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data_sets = self.data_sets()
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# Rename columns:
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renaming_dict = {
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data_set.input_field: data_set.renamed_field for data_set in data_sets
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data_set.input_field: data_set.renamed_field
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for data_set in data_sets
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}
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self.df.rename(
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@ -307,13 +320,6 @@ class ScoreETL(ExtractTransformLoad):
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self.df[data_set.renamed_field] - min_value
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) / (max_value - min_value)
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# Graph distributions and correlations.
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min_max_fields = [ # noqa: F841
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f"{data_set.renamed_field}{self.MIN_MAX_FIELD_SUFFIX}"
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for data_set in data_sets
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if data_set.renamed_field != self.GEOID_FIELD_NAME
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]
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# Calculate score "A" and score "B"
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self.df["Score A"] = self.df[
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[
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@ -322,7 +328,9 @@ class ScoreETL(ExtractTransformLoad):
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]
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].mean(axis=1)
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self.df["Score B"] = (
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self.df["Poverty (Less than 200% of federal poverty line) (percentile)"]
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self.df[
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"Poverty (Less than 200% of federal poverty line) (percentile)"
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]
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* self.df[
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"Percent individuals age 25 or over with less than high school degree (percentile)"
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]
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@ -357,7 +365,8 @@ class ScoreETL(ExtractTransformLoad):
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# Multiply the "Pollution Burden" score and the "Population Characteristics"
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# together to produce the cumulative impact score.
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self.df["Score C"] = (
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self.df[self.AGGREGATION_POLLUTION] * self.df[self.AGGREGATION_POPULATION]
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self.df[self.AGGREGATION_POLLUTION]
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* self.df[self.AGGREGATION_POPULATION]
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)
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if len(census_block_group_df) > 220333:
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@ -372,10 +381,12 @@ class ScoreETL(ExtractTransformLoad):
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]
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fields_min_max = [
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f"{field}{self.MIN_MAX_FIELD_SUFFIX}" for field in fields_to_use_in_score
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f"{field}{self.MIN_MAX_FIELD_SUFFIX}"
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for field in fields_to_use_in_score
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]
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fields_percentile = [
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f"{field}{self.PERCENTILE_FIELD_SUFFIX}" for field in fields_to_use_in_score
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f"{field}{self.PERCENTILE_FIELD_SUFFIX}"
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for field in fields_to_use_in_score
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]
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# Calculate "Score D", which uses min-max normalization
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@ -428,10 +439,10 @@ class ScoreETL(ExtractTransformLoad):
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) | (self.df["Respiratory hazard " "index"] > 0.75)
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self.df["Score F (communities)"] = (
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self.df[ami_and_high_school_field_name] & self.df[meets_burden_field_name]
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self.df[ami_and_high_school_field_name]
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& self.df[meets_burden_field_name]
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)
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def load(self) -> None:
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logger.info("Saving Score CSV")
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@ -439,6 +450,8 @@ class ScoreETL(ExtractTransformLoad):
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self.SCORE_CSV_PATH.mkdir(parents=True, exist_ok=True)
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# TODO: drop
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self.df[0:10000].to_csv(self.SCORE_CSV_PATH / "usa-10000.csv", index=False)
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self.df[0:10000].to_csv(
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self.SCORE_CSV_PATH / "usa-10000.csv", index=False
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)
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self.df.to_csv(self.SCORE_CSV_PATH / "usa.csv", index=False)
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@ -41,16 +41,32 @@ class PostScoreETL(ExtractTransformLoad):
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self.TILES_SCORE_COLUMNS = [
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"GEOID10",
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"State Name",
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"County Name",
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"Total population",
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"Score E (percentile)",
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"Score E (top 25th percentile)",
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"GEOID",
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"State Abbreviation",
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"County Name",
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"Poverty (Less than 200% of federal poverty line)",
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"Percent individuals age 25 or over with less than high school degree",
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"Linguistic isolation (percent)",
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"Unemployed civilians (percent)",
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"Housing burden (percent)",
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]
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self.TILES_SCORE_CSV_PATH = self.SCORE_CSV_PATH / "tiles"
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self.TILES_SCORE_CSV = self.TILES_SCORE_CSV_PATH / "usa.csv"
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# These are the
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# columns to round floats to 2 decimals
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self.TILES_SCORE_FLOAT_COLUMNS = [
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"Score E (percentile)",
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"Score E (top 25th percentile)",
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"Poverty (Less than 200% of federal poverty line)",
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"Percent individuals age 25 or over with less than high school degree",
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"Linguistic isolation (percent)",
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"Unemployed civilians (percent)",
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"Housing burden (percent)",
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]
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self.TILES_ROUND_NUM_DECIMALS = 2
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self.DOWNLOADABLE_SCORE_INDICATORS_BASIC = [
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"Percent individuals age 25 or over with less than high school degree",
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"Linguistic isolation (percent)",
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@ -106,7 +122,10 @@ class PostScoreETL(ExtractTransformLoad):
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self.counties_df = pd.read_csv(
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self.CENSUS_COUNTIES_TXT,
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sep="\t",
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dtype={"GEOID": "string", "USPS": "string"},
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dtype={
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"GEOID": "string",
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"USPS": "string",
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},
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low_memory=False,
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encoding="latin-1",
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)
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@ -115,7 +134,10 @@ class PostScoreETL(ExtractTransformLoad):
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self.states_df = pd.read_csv(
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self.STATE_CSV, dtype={"fips": "string", "state_code": "string"}
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)
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self.score_df = pd.read_csv(self.FULL_SCORE_CSV, dtype={"GEOID10": "string"})
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self.score_df = pd.read_csv(
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self.FULL_SCORE_CSV,
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dtype={"GEOID10": "string", "Total population": "int64"},
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)
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def transform(self) -> None:
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logger.info("Transforming data sources for Score + County CSV")
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@ -165,13 +187,22 @@ class PostScoreETL(ExtractTransformLoad):
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# merge census cbgs with score
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merged_df = cbg_usa_df.merge(
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self.score_county_state_merged, on="GEOID10", how="left"
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self.score_county_state_merged,
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on="GEOID10",
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how="left",
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)
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# recast population to integer
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merged_df["Total population"] = (
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merged_df["Total population"].fillna(0.0).astype(int)
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)
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# list the null score cbgs
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null_cbg_df = merged_df[merged_df["Score E (percentile)"].isnull()]
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# subsctract data sets
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# this follows the XOR pattern outlined here:
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# https://stackoverflow.com/a/37313953
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removed_df = pd.concat([merged_df, null_cbg_df, null_cbg_df]).drop_duplicates(
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keep=False
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)
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@ -188,9 +219,14 @@ class PostScoreETL(ExtractTransformLoad):
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def _save_tile_csv(self):
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logger.info("Saving Tile Score CSV")
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# TODO: check which are the columns we'll use
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# Related to: https://github.com/usds/justice40-tool/issues/302
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score_tiles = self.score_county_state_merged[self.TILES_SCORE_COLUMNS]
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decimals = pd.Series(
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[self.TILES_ROUND_NUM_DECIMALS] * len(self.TILES_SCORE_FLOAT_COLUMNS),
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index=self.TILES_SCORE_FLOAT_COLUMNS,
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)
|
||||
score_tiles = score_tiles.round(decimals)
|
||||
|
||||
self.TILES_SCORE_CSV_PATH.mkdir(parents=True, exist_ok=True)
|
||||
score_tiles.to_csv(self.TILES_SCORE_CSV, index=False)
|
||||
|
||||
|
|
@ -210,7 +246,10 @@ class PostScoreETL(ExtractTransformLoad):
|
|||
downloadable_tiles.to_excel(self.DOWNLOADABLE_SCORE_EXCEL, index=False)
|
||||
|
||||
logger.info("Compressing files")
|
||||
files_to_compress = [self.DOWNLOADABLE_SCORE_CSV, self.DOWNLOADABLE_SCORE_EXCEL]
|
||||
files_to_compress = [
|
||||
self.DOWNLOADABLE_SCORE_CSV,
|
||||
self.DOWNLOADABLE_SCORE_EXCEL,
|
||||
]
|
||||
with zipfile.ZipFile(self.DOWNLOADABLE_SCORE_ZIP, "w") as zf:
|
||||
for f in files_to_compress:
|
||||
zf.write(f, arcname=Path(f).name, compress_type=compression)
|
||||
|
|
|
|||
176
data/data-pipeline/poetry.lock
generated
176
data/data-pipeline/poetry.lock
generated
|
|
@ -137,7 +137,7 @@ webencodings = "*"
|
|||
|
||||
[[package]]
|
||||
name = "censusdata"
|
||||
version = "1.14"
|
||||
version = "1.15"
|
||||
description = "Download data from U.S. Census API"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -518,6 +518,14 @@ parso = ">=0.8.0,<0.9.0"
|
|||
qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
|
||||
testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<6.0.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "jellyfish"
|
||||
version = "0.6.1"
|
||||
description = "a library for doing approximate and phonetic matching of strings."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "jinja2"
|
||||
version = "3.0.1"
|
||||
|
|
@ -908,7 +916,7 @@ python-versions = ">=3.5"
|
|||
|
||||
[[package]]
|
||||
name = "notebook"
|
||||
version = "6.4.0"
|
||||
version = "6.4.2"
|
||||
description = "A web-based notebook environment for interactive computing"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -1139,6 +1147,14 @@ isort = ">=4.2.5,<6"
|
|||
mccabe = ">=0.6,<0.7"
|
||||
toml = ">=0.7.1"
|
||||
|
||||
[[package]]
|
||||
name = "pypandoc"
|
||||
version = "1.6.3"
|
||||
description = "Thin wrapper for pandoc."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "pyparsing"
|
||||
version = "2.4.7"
|
||||
|
|
@ -1233,7 +1249,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
|
|||
|
||||
[[package]]
|
||||
name = "pyzmq"
|
||||
version = "22.2.0"
|
||||
version = "22.2.1"
|
||||
description = "Python bindings for 0MQ"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -1323,13 +1339,15 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
|
|||
|
||||
[[package]]
|
||||
name = "send2trash"
|
||||
version = "1.7.1"
|
||||
version = "1.8.0"
|
||||
description = "Send file to trash natively under Mac OS X, Windows and Linux."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[package.extras]
|
||||
nativelib = ["pyobjc-framework-cocoa", "pywin32"]
|
||||
objc = ["pyobjc-framework-cocoa"]
|
||||
win32 = ["pywin32"]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -1390,7 +1408,7 @@ python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
|
|||
|
||||
[[package]]
|
||||
name = "tomli"
|
||||
version = "1.2.0"
|
||||
version = "1.2.1"
|
||||
description = "A lil' TOML parser"
|
||||
category = "dev"
|
||||
optional = false
|
||||
|
|
@ -1427,6 +1445,22 @@ virtualenv = ">=16.0.0,<20.0.0 || >20.0.0,<20.0.1 || >20.0.1,<20.0.2 || >20.0.2,
|
|||
docs = ["pygments-github-lexers (>=0.0.5)", "sphinx (>=2.0.0)", "sphinxcontrib-autoprogram (>=0.1.5)", "towncrier (>=18.5.0)"]
|
||||
testing = ["flaky (>=3.4.0)", "freezegun (>=0.3.11)", "psutil (>=5.6.1)", "pytest (>=4.0.0)", "pytest-cov (>=2.5.1)", "pytest-mock (>=1.10.0)", "pytest-randomly (>=1.0.0)", "pytest-xdist (>=1.22.2)", "pathlib2 (>=2.3.3)"]
|
||||
|
||||
[[package]]
|
||||
name = "tqdm"
|
||||
version = "4.62.0"
|
||||
description = "Fast, Extensible Progress Meter"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
|
||||
|
||||
[package.dependencies]
|
||||
colorama = {version = "*", markers = "platform_system == \"Windows\""}
|
||||
|
||||
[package.extras]
|
||||
dev = ["py-make (>=0.1.0)", "twine", "wheel"]
|
||||
notebook = ["ipywidgets (>=6)"]
|
||||
telegram = ["requests"]
|
||||
|
||||
[[package]]
|
||||
name = "traitlets"
|
||||
version = "5.0.5"
|
||||
|
|
@ -1451,7 +1485,7 @@ python-versions = "*"
|
|||
|
||||
[[package]]
|
||||
name = "types-requests"
|
||||
version = "2.25.2"
|
||||
version = "2.25.6"
|
||||
description = "Typing stubs for requests"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -1478,9 +1512,20 @@ brotli = ["brotlipy (>=0.6.0)"]
|
|||
secure = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "certifi", "ipaddress"]
|
||||
socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "us"
|
||||
version = "2.0.2"
|
||||
description = "US state meta information and other fun stuff"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[package.dependencies]
|
||||
jellyfish = "0.6.1"
|
||||
|
||||
[[package]]
|
||||
name = "virtualenv"
|
||||
version = "20.7.0"
|
||||
version = "20.7.1"
|
||||
description = "Virtual Python Environment builder"
|
||||
category = "dev"
|
||||
optional = false
|
||||
|
|
@ -1533,6 +1578,14 @@ category = "dev"
|
|||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "xlsxwriter"
|
||||
version = "2.0.0"
|
||||
description = "A Python module for creating Excel XLSX files."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.5.0"
|
||||
|
|
@ -1548,7 +1601,7 @@ testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytes
|
|||
[metadata]
|
||||
lock-version = "1.1"
|
||||
python-versions = "^3.7.1"
|
||||
content-hash = "7380a36633c41b57d351df2facdf3a5fd05dfc9f0dc4f629d5f3dfec61181c6b"
|
||||
content-hash = "14f5225f41212af2785865f984c8ce402712df0398b59c460cb849a0792b3f17"
|
||||
|
||||
[metadata.files]
|
||||
appdirs = [
|
||||
|
|
@ -1616,7 +1669,7 @@ bleach = [
|
|||
{file = "bleach-4.0.0.tar.gz", hash = "sha256:ffa9221c6ac29399cc50fcc33473366edd0cf8d5e2cbbbb63296dc327fb67cc8"},
|
||||
]
|
||||
censusdata = [
|
||||
{file = "CensusData-1.14.tar.gz", hash = "sha256:fd7bf06c797070d23df98cbaa60897ee98b265724e6d582b421b25f0f4cfcff6"},
|
||||
{file = "CensusData-1.15.tar.gz", hash = "sha256:0ccbdeede9d5475530ae04f13a9893809617ed83d1577d8207b72fdb782c8b39"},
|
||||
]
|
||||
certifi = [
|
||||
{file = "certifi-2021.5.30-py2.py3-none-any.whl", hash = "sha256:50b1e4f8446b06f41be7dd6338db18e0990601dce795c2b1686458aa7e8fa7d8"},
|
||||
|
|
@ -1833,6 +1886,9 @@ jedi = [
|
|||
{file = "jedi-0.18.0-py2.py3-none-any.whl", hash = "sha256:18456d83f65f400ab0c2d3319e48520420ef43b23a086fdc05dff34132f0fb93"},
|
||||
{file = "jedi-0.18.0.tar.gz", hash = "sha256:92550a404bad8afed881a137ec9a461fed49eca661414be45059329614ed0707"},
|
||||
]
|
||||
jellyfish = [
|
||||
{file = "jellyfish-0.6.1.tar.gz", hash = "sha256:5104e45a2b804b48a46a92a5e6d6e86830fe60ae83b1da32c867402c8f4c2094"},
|
||||
]
|
||||
jinja2 = [
|
||||
{file = "Jinja2-3.0.1-py3-none-any.whl", hash = "sha256:1f06f2da51e7b56b8f238affdd6b4e2c61e39598a378cc49345bc1bd42a978a4"},
|
||||
{file = "Jinja2-3.0.1.tar.gz", hash = "sha256:703f484b47a6af502e743c9122595cc812b0271f661722403114f71a79d0f5a4"},
|
||||
|
|
@ -2058,8 +2114,8 @@ nest-asyncio = [
|
|||
{file = "nest_asyncio-1.5.1.tar.gz", hash = "sha256:afc5a1c515210a23c461932765691ad39e8eba6551c055ac8d5546e69250d0aa"},
|
||||
]
|
||||
notebook = [
|
||||
{file = "notebook-6.4.0-py3-none-any.whl", hash = "sha256:f7f0a71a999c7967d9418272ae4c3378a220bd28330fbfb49860e46cf8a5838a"},
|
||||
{file = "notebook-6.4.0.tar.gz", hash = "sha256:9c4625e2a2aa49d6eae4ce20cbc3d8976db19267e32d2a304880e0c10bf8aef9"},
|
||||
{file = "notebook-6.4.2-py3-none-any.whl", hash = "sha256:5ae23d7f831a5788e8bd51a0ba65c486db3bfd43e9db97a62330b6273e3175e3"},
|
||||
{file = "notebook-6.4.2.tar.gz", hash = "sha256:ba9db5e5a9bd2d272b67e3de9143cca2be5125578f1c4f2902d7178ce2f0b4ff"},
|
||||
]
|
||||
numpy = [
|
||||
{file = "numpy-1.21.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:38e8648f9449a549a7dfe8d8755a5979b45b3538520d1e735637ef28e8c2dc50"},
|
||||
|
|
@ -2183,6 +2239,10 @@ pylint = [
|
|||
{file = "pylint-2.9.6-py3-none-any.whl", hash = "sha256:2e1a0eb2e8ab41d6b5dbada87f066492bb1557b12b76c47c2ee8aa8a11186594"},
|
||||
{file = "pylint-2.9.6.tar.gz", hash = "sha256:8b838c8983ee1904b2de66cce9d0b96649a91901350e956d78f289c3bc87b48e"},
|
||||
]
|
||||
pypandoc = [
|
||||
{file = "pypandoc-1.6.3-py3-none-win_amd64.whl", hash = "sha256:ed2178f0bfc77e565678c10dd7b57143af01a28d6f9d035995518b5e5b7b877b"},
|
||||
{file = "pypandoc-1.6.3.tar.gz", hash = "sha256:95a331f5ef74adb9557e9961d784c30ba73bd0d62e7736bb5d9ce74888b9f438"},
|
||||
]
|
||||
pyparsing = [
|
||||
{file = "pyparsing-2.4.7-py2.py3-none-any.whl", hash = "sha256:ef9d7589ef3c200abe66653d3f1ab1033c3c419ae9b9bdb1240a85b024efc88b"},
|
||||
{file = "pyparsing-2.4.7.tar.gz", hash = "sha256:c203ec8783bf771a155b207279b9bccb8dea02d8f0c9e5f8ead507bc3246ecc1"},
|
||||
|
|
@ -2294,36 +2354,43 @@ pyyaml = [
|
|||
{file = "PyYAML-5.4.1.tar.gz", hash = "sha256:607774cbba28732bfa802b54baa7484215f530991055bb562efbed5b2f20a45e"},
|
||||
]
|
||||
pyzmq = [
|
||||
{file = "pyzmq-22.2.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:127b8727911331377af63f014c334059a440f9543f03305d244faaf281c9f108"},
|
||||
{file = "pyzmq-22.2.0-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f0130c3596782b3a8a0522cc8bfaff6472fdd09e7e2ef99476029f9788896888"},
|
||||
{file = "pyzmq-22.2.0-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9aba658e4f2e975a9a7ec6f090a5e35a57591720bd6c192e5d3ab1789e1c57b4"},
|
||||
{file = "pyzmq-22.2.0-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:ec916dadd5709e875925bef5c811c87ffc0188a16333c1cce3b6a13b088b37a7"},
|
||||
{file = "pyzmq-22.2.0-cp36-cp36m-win32.whl", hash = "sha256:6a138dad866ee34957806f99f2cf59bc016db7a0be5eae27cfbde1c3a78294e6"},
|
||||
{file = "pyzmq-22.2.0-cp36-cp36m-win_amd64.whl", hash = "sha256:6bd3e6506a5fad7d6edefbf0237581f1d775b0722fa2079cae346270f7b8f5e4"},
|
||||
{file = "pyzmq-22.2.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:69866d133c60c865b74406f332d23de1d69963efaa676453ab9c870a73c62240"},
|
||||
{file = "pyzmq-22.2.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:229916a3bf2bb04833e79fa5dda135f852bd13e66562b4945628dd3d6e88a7ee"},
|
||||
{file = "pyzmq-22.2.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1c35f9c938af2d665af9f2e89b04c5d2218ab2dca14d549cdf54c5f673c70a65"},
|
||||
{file = "pyzmq-22.2.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:50f6b89dc518b8dddfc3419fe85179bc9cba363f6c1c6efd11b4107914230dbb"},
|
||||
{file = "pyzmq-22.2.0-cp37-cp37m-win32.whl", hash = "sha256:5cd2141bcba00d0f13f89ef48024d7482aaf21302dc57de049b90be648819caf"},
|
||||
{file = "pyzmq-22.2.0-cp37-cp37m-win_amd64.whl", hash = "sha256:af291a9ffb25a3e14f44dc4f5127d59fbfb5ef68333df9af630126fc4cb92000"},
|
||||
{file = "pyzmq-22.2.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:8663aa3d058ba9cd9ade9655b94b8d836052a29189f6dcf78735eeec19f4d5f1"},
|
||||
{file = "pyzmq-22.2.0-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:50a463a2d72773cf5f601bdb562cd1d8fd63e68a7eeda9ba4f3748d71ff385bd"},
|
||||
{file = "pyzmq-22.2.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:198d2c691c0cee06714a5fdb904fa42f19fa62822d24b4037e8198775e8d2a6d"},
|
||||
{file = "pyzmq-22.2.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6a0c468bf60392cf1eb025f8bb5d7dfe2c8898fcfdef6c098ca369a57e65028f"},
|
||||
{file = "pyzmq-22.2.0-cp38-cp38-win32.whl", hash = "sha256:6266a3d62d9ffbe81ab786b4ee079fd0a43620b009a14879afd094dd551c1a6e"},
|
||||
{file = "pyzmq-22.2.0-cp38-cp38-win_amd64.whl", hash = "sha256:206c9366ba308dba68be19cd187b2550bc4cea1b80d2aa19cb1356a1c2c173f6"},
|
||||
{file = "pyzmq-22.2.0-cp39-cp39-macosx_10_15_universal2.whl", hash = "sha256:78bfa1dddf623294165e7647bf6378dd8d7c1945c8dfb8535c74eef6a5841b89"},
|
||||
{file = "pyzmq-22.2.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c4840a8ba94c65a44fabf439d8d9973f8e130fe4dd2cb722fd786c8c1f034754"},
|
||||
{file = "pyzmq-22.2.0-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:2dd9a7472069ca2b0865a8a2aea80e31f9c8e49193afbf4f929900e491122418"},
|
||||
{file = "pyzmq-22.2.0-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:e04af13ee1b34146b05273cafe7b8367dd2f39a58fcd4956dcc7263018fc7074"},
|
||||
{file = "pyzmq-22.2.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9445f44b51fe3a3f138bc2e13ac5a1f1875df6bb3445ae2044d69962bbf69acd"},
|
||||
{file = "pyzmq-22.2.0-cp39-cp39-win32.whl", hash = "sha256:7d042f1e58779d0301cc0efbe462ad818f1ff01e13992d08b0b9167c170f713c"},
|
||||
{file = "pyzmq-22.2.0-cp39-cp39-win_amd64.whl", hash = "sha256:f2943ad121f880f4b89be952d3a49c3ea39ba6e02abe6d3c8029331602a33b91"},
|
||||
{file = "pyzmq-22.2.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:1068ab72e78a1279a2b8c1607234d0999f90773d9981e7c80ed35e3bf2f4ccfc"},
|
||||
{file = "pyzmq-22.2.0-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:2776ccc2f693cc9d5e89e4432e2e0c067499bf6621aec6961a5d894dd0f042be"},
|
||||
{file = "pyzmq-22.2.0-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:37513cb842e2fd3e7c15141ef4e4152ef94c0a35269a62cabf6f2aaef3a59b30"},
|
||||
{file = "pyzmq-22.2.0-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:daf87bc30e4a00aca33b1b1e10414246f4f5714c39db04be0e498fae1ab1e767"},
|
||||
{file = "pyzmq-22.2.0.tar.gz", hash = "sha256:ff6454bd8067463380ea992a7cbe623bd61aeb83a8f19d47eb221eec3f798080"},
|
||||
{file = "pyzmq-22.2.1-cp310-cp310-macosx_10_15_universal2.whl", hash = "sha256:d60a407663b7c2af781ab7f49d94a3d379dd148bb69ea8d9dd5bc69adf18097c"},
|
||||
{file = "pyzmq-22.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:631f932fb1fa4b76f31adf976f8056519bc6208a3c24c184581c3dd5be15066e"},
|
||||
{file = "pyzmq-22.2.1-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:0471d634c7fe48ff7d3849798da6c16afc71676dd890b5ae08eb1efe735c6fec"},
|
||||
{file = "pyzmq-22.2.1-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:f520e9fee5d7a2e09b051d924f85b977c6b4e224e56c0551c3c241bbeeb0ad8d"},
|
||||
{file = "pyzmq-22.2.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c1b6619ceb33a8907f1cb82ff8afc8a133e7a5f16df29528e919734718600426"},
|
||||
{file = "pyzmq-22.2.1-cp310-cp310-win32.whl", hash = "sha256:31c5dfb6df5148789835128768c01bf6402eb753d06f524f12f6786caf96fb44"},
|
||||
{file = "pyzmq-22.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:4842a8263cbaba6fce401bbe4e2b125321c401a01714e42624dabc554bfc2629"},
|
||||
{file = "pyzmq-22.2.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:b921758f8b5098faa85f341bbdd5e36d5339de5e9032ca2b07d8c8e7bec5069b"},
|
||||
{file = "pyzmq-22.2.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:240b83b3a8175b2f616f80092cbb019fcd5c18598f78ffc6aa0ae9034b300f14"},
|
||||
{file = "pyzmq-22.2.1-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:da7f7f3bb08bcf59a6b60b4e53dd8f08bb00c9e61045319d825a906dbb3c8fb7"},
|
||||
{file = "pyzmq-22.2.1-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:e66025b64c4724ba683d6d4a4e5ee23de12fe9ae683908f0c7f0f91b4a2fd94e"},
|
||||
{file = "pyzmq-22.2.1-cp36-cp36m-win32.whl", hash = "sha256:50d007d5702171bc810c1e74498fa2c7bc5b50f9750697f7fd2a3e71a25aad91"},
|
||||
{file = "pyzmq-22.2.1-cp36-cp36m-win_amd64.whl", hash = "sha256:b4a51c7d906dc263a0cc5590761e53e0a68f2c2fefe549cbef21c9ee5d2d98a4"},
|
||||
{file = "pyzmq-22.2.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:93705cb90baa9d6f75e8448861a1efd3329006f79095ab18846bd1eaa342f7c3"},
|
||||
{file = "pyzmq-22.2.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:620b0abb813958cb3ecb5144c177e26cde92fee6f43c4b9de6b329515532bf27"},
|
||||
{file = "pyzmq-22.2.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2dd3896b3c952cf6c8013deda53c1df16bf962f355b5503d23521e0f6403ae3d"},
|
||||
{file = "pyzmq-22.2.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:6e9c030222893afa86881d7485d3e841969760a16004bd23e9a83cca28b42778"},
|
||||
{file = "pyzmq-22.2.1-cp37-cp37m-win32.whl", hash = "sha256:262f470e7acde18b7217aac78d19d2e29ced91a5afbeb7d98521ebf26461aa7e"},
|
||||
{file = "pyzmq-22.2.1-cp37-cp37m-win_amd64.whl", hash = "sha256:246f27b88722cfa729bb04881e94484e40b085720d728c1b05133b3f331b0b7b"},
|
||||
{file = "pyzmq-22.2.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:0d17bac19e934e9f547a8811b7c2a32651a7840f38086b924e2e3dcb2fae5c3a"},
|
||||
{file = "pyzmq-22.2.1-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:5933d1f4087de6e52906f72d92e1e4dcc630d371860b92c55d7f7a4b815a664c"},
|
||||
{file = "pyzmq-22.2.1-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:ac4497e4b7d134ee53ce5532d9cc3b640d6e71806a55062984e0c99a2f88f465"},
|
||||
{file = "pyzmq-22.2.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:66375a6094af72a6098ed4403b15b4db6bf00013c6febc1baa832e7abda827f4"},
|
||||
{file = "pyzmq-22.2.1-cp38-cp38-win32.whl", hash = "sha256:b2c16d20bd0aef8e57bc9505fdd80ea0d6008020c3740accd96acf1b3d1b5347"},
|
||||
{file = "pyzmq-22.2.1-cp38-cp38-win_amd64.whl", hash = "sha256:ff345d48940c834168f81fa1d4724675099f148f1ab6369748c4d712ed71bf7c"},
|
||||
{file = "pyzmq-22.2.1-cp39-cp39-macosx_10_15_universal2.whl", hash = "sha256:f5c84c5de9a773bbf8b22c51e28380999ea72e5e85b4db8edf5e69a7a0d4d9f9"},
|
||||
{file = "pyzmq-22.2.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:2534a036b777f957bd6b89b55fb2136775ca2659fb0f1c85036ba78d17d86fd5"},
|
||||
{file = "pyzmq-22.2.1-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:a649065413ba4eab92a783a7caa4de8ce14cf46ba8a2a09951426143f1298adb"},
|
||||
{file = "pyzmq-22.2.1-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:c9cb0bd3a3cb7ccad3caa1d7b0d18ba71ed3a4a3610028e506a4084371d4d223"},
|
||||
{file = "pyzmq-22.2.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b4428302c389fffc0c9c07a78cad5376636b9d096f332acfe66b321ae9ff2c63"},
|
||||
{file = "pyzmq-22.2.1-cp39-cp39-win32.whl", hash = "sha256:6a5b4566f66d953601d0d47d4071897f550a265bafd52ebcad5ac7aad3838cbb"},
|
||||
{file = "pyzmq-22.2.1-cp39-cp39-win_amd64.whl", hash = "sha256:89200ab6ef9081c72a04ed84c52a50b60dcb0655375aeedb40689bc7c934715e"},
|
||||
{file = "pyzmq-22.2.1-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:ed67df4eaa99a20d162d76655bda23160abdf8abf82a17f41dfd3962e608dbcc"},
|
||||
{file = "pyzmq-22.2.1-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:021e22a8c58ab294bd4b96448a2ca4e716e1d76600192ff84c33d71edb1fbd37"},
|
||||
{file = "pyzmq-22.2.1-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:200ac096cee5499964c90687306a7244b79ef891f773ed4cf15019fd1f3df330"},
|
||||
{file = "pyzmq-22.2.1-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:b3f57bee62e36be5c97712de32237c5589caee0d1154c2ad01a888accfae20bc"},
|
||||
{file = "pyzmq-22.2.1.tar.gz", hash = "sha256:6d18c76676771fd891ca8e0e68da0bbfb88e30129835c0ade748016adb3b6242"},
|
||||
]
|
||||
qtconsole = [
|
||||
{file = "qtconsole-5.1.1-py3-none-any.whl", hash = "sha256:73994105b0369bb99f4164df4a131010f3c7b33a7b5169c37366358d8744675b"},
|
||||
|
|
@ -2381,8 +2448,8 @@ semantic-version = [
|
|||
{file = "semantic_version-2.8.5.tar.gz", hash = "sha256:d2cb2de0558762934679b9a104e82eca7af448c9f4974d1f3eeccff651df8a54"},
|
||||
]
|
||||
send2trash = [
|
||||
{file = "Send2Trash-1.7.1-py3-none-any.whl", hash = "sha256:c20fee8c09378231b3907df9c215ec9766a84ee20053d99fbad854fe8bd42159"},
|
||||
{file = "Send2Trash-1.7.1.tar.gz", hash = "sha256:17730aa0a33ab82ed6ca76be3bb25f0433d0014f1ccf63c979bab13a5b9db2b2"},
|
||||
{file = "Send2Trash-1.8.0-py3-none-any.whl", hash = "sha256:f20eaadfdb517eaca5ce077640cb261c7d2698385a6a0f072a4a5447fd49fa08"},
|
||||
{file = "Send2Trash-1.8.0.tar.gz", hash = "sha256:d2c24762fd3759860a0aff155e45871447ea58d2be6bdd39b5c8f966a0c99c2d"},
|
||||
]
|
||||
shapely = [
|
||||
{file = "Shapely-1.7.1-1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:46da0ea527da9cf9503e66c18bab6981c5556859e518fe71578b47126e54ca93"},
|
||||
|
|
@ -2426,8 +2493,8 @@ toml = [
|
|||
{file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
|
||||
]
|
||||
tomli = [
|
||||
{file = "tomli-1.2.0-py3-none-any.whl", hash = "sha256:056f0376bf5a6b182c513f9582c1e5b0487265eb6c48842b69aa9ca1cd5f640a"},
|
||||
{file = "tomli-1.2.0.tar.gz", hash = "sha256:d60e681734099207a6add7a10326bc2ddd1fdc36c1b0f547d00ef73ac63739c2"},
|
||||
{file = "tomli-1.2.1-py3-none-any.whl", hash = "sha256:8dd0e9524d6f386271a36b41dbf6c57d8e32fd96fd22b6584679dc569d20899f"},
|
||||
{file = "tomli-1.2.1.tar.gz", hash = "sha256:a5b75cb6f3968abb47af1b40c1819dc519ea82bcc065776a866e8d74c5ca9442"},
|
||||
]
|
||||
tornado = [
|
||||
{file = "tornado-6.1-cp35-cp35m-macosx_10_9_x86_64.whl", hash = "sha256:d371e811d6b156d82aa5f9a4e08b58debf97c302a35714f6f45e35139c332e32"},
|
||||
|
|
@ -2476,6 +2543,10 @@ tox = [
|
|||
{file = "tox-3.24.1-py2.py3-none-any.whl", hash = "sha256:60eda26fa47b7130e6fc1145620b1fd897963af521093c3685c3f63d1c394029"},
|
||||
{file = "tox-3.24.1.tar.gz", hash = "sha256:9850daeb96d21b4abf049bc5f197426123039e383ebfed201764e9355fc5a880"},
|
||||
]
|
||||
tqdm = [
|
||||
{file = "tqdm-4.62.0-py2.py3-none-any.whl", hash = "sha256:706dea48ee05ba16e936ee91cb3791cd2ea6da348a0e50b46863ff4363ff4340"},
|
||||
{file = "tqdm-4.62.0.tar.gz", hash = "sha256:3642d483b558eec80d3c831e23953582c34d7e4540db86d9e5ed9dad238dabc6"},
|
||||
]
|
||||
traitlets = [
|
||||
{file = "traitlets-5.0.5-py3-none-any.whl", hash = "sha256:69ff3f9d5351f31a7ad80443c2674b7099df13cc41fc5fa6e2f6d3b0330b0426"},
|
||||
{file = "traitlets-5.0.5.tar.gz", hash = "sha256:178f4ce988f69189f7e523337a3e11d91c786ded9360174a3d9ca83e79bc5396"},
|
||||
|
|
@ -2513,8 +2584,8 @@ typed-ast = [
|
|||
{file = "typed_ast-1.4.3.tar.gz", hash = "sha256:fb1bbeac803adea29cedd70781399c99138358c26d05fcbd23c13016b7f5ec65"},
|
||||
]
|
||||
types-requests = [
|
||||
{file = "types-requests-2.25.2.tar.gz", hash = "sha256:03122b582f5300ec35ac6692f2634207c467e602dc9ba46b5811a9f6ce0b0bc2"},
|
||||
{file = "types_requests-2.25.2-py3-none-any.whl", hash = "sha256:a4c03c654527957a70002079ca48669b53d82eac4811abf140ea93847b65529b"},
|
||||
{file = "types-requests-2.25.6.tar.gz", hash = "sha256:e21541c0f55c066c491a639309159556dd8c5833e49fcde929c4c47bdb0002ee"},
|
||||
{file = "types_requests-2.25.6-py3-none-any.whl", hash = "sha256:a5a305b43ea57bf64d6731f89816946a405b591eff6de28d4c0fd58422cee779"},
|
||||
]
|
||||
typing-extensions = [
|
||||
{file = "typing_extensions-3.10.0.0-py2-none-any.whl", hash = "sha256:0ac0f89795dd19de6b97debb0c6af1c70987fd80a2d62d1958f7e56fcc31b497"},
|
||||
|
|
@ -2525,9 +2596,12 @@ urllib3 = [
|
|||
{file = "urllib3-1.26.6-py2.py3-none-any.whl", hash = "sha256:39fb8672126159acb139a7718dd10806104dec1e2f0f6c88aab05d17df10c8d4"},
|
||||
{file = "urllib3-1.26.6.tar.gz", hash = "sha256:f57b4c16c62fa2760b7e3d97c35b255512fb6b59a259730f36ba32ce9f8e342f"},
|
||||
]
|
||||
us = [
|
||||
{file = "us-2.0.2.tar.gz", hash = "sha256:cb11ad0d43deff3a1c3690c74f0c731cff5b862c73339df2edd91133e1496fbc"},
|
||||
]
|
||||
virtualenv = [
|
||||
{file = "virtualenv-20.7.0-py2.py3-none-any.whl", hash = "sha256:fdfdaaf0979ac03ae7f76d5224a05b58165f3c804f8aa633f3dd6f22fbd435d5"},
|
||||
{file = "virtualenv-20.7.0.tar.gz", hash = "sha256:97066a978431ec096d163e72771df5357c5c898ffdd587048f45e0aecc228094"},
|
||||
{file = "virtualenv-20.7.1-py2.py3-none-any.whl", hash = "sha256:73863dc3be1efe6ee638e77495c0c195a6384ae7b15c561f3ceb2698ae7267c1"},
|
||||
{file = "virtualenv-20.7.1.tar.gz", hash = "sha256:57bcb59c5898818bd555b1e0cfcf668bd6204bc2b53ad0e70a52413bd790f9e4"},
|
||||
]
|
||||
wcwidth = [
|
||||
{file = "wcwidth-0.2.5-py2.py3-none-any.whl", hash = "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784"},
|
||||
|
|
@ -2544,6 +2618,10 @@ widgetsnbextension = [
|
|||
wrapt = [
|
||||
{file = "wrapt-1.12.1.tar.gz", hash = "sha256:b62ffa81fb85f4332a4f609cab4ac40709470da05643a082ec1eb88e6d9b97d7"},
|
||||
]
|
||||
xlsxwriter = [
|
||||
{file = "XlsxWriter-2.0.0-py2.py3-none-any.whl", hash = "sha256:51fbb1d727d8391ddf240ce665710d6b205944dc84842c7b8452ac40226eeb71"},
|
||||
{file = "XlsxWriter-2.0.0.tar.gz", hash = "sha256:80ce4aadc638dea452f6e28f70b6223b9b5b5740ff9c57ef6387af115e129bbb"},
|
||||
]
|
||||
zipp = [
|
||||
{file = "zipp-3.5.0-py3-none-any.whl", hash = "sha256:957cfda87797e389580cb8b9e3870841ca991e2125350677b2ca83a0e99390a3"},
|
||||
{file = "zipp-3.5.0.tar.gz", hash = "sha256:f5812b1e007e48cff63449a5e9f4e7ebea716b4111f9c4f9a645f91d579bf0c4"},
|
||||
|
|
|
|||
|
|
@ -12,7 +12,6 @@ geopandas = "^0.9.0"
|
|||
ipython = "^7.24.1"
|
||||
jupyter = "^1.0.0"
|
||||
jupyter-contrib-nbextensions = "^0.5.1"
|
||||
matplotlib = "^3.4.2"
|
||||
numpy = "^1.21.0"
|
||||
pandas = "^1.2.5"
|
||||
python = "^3.7.1"
|
||||
|
|
|
|||
|
|
@ -1,44 +1,32 @@
|
|||
appdirs==1.4.4; python_full_version >= "3.6.2"
|
||||
appnope==0.1.2; sys_platform == "darwin" and python_version >= "3.7" and platform_system == "Darwin"
|
||||
argon2-cffi==20.1.0; python_version >= "3.6"
|
||||
astroid==2.6.6; python_version >= "3.6" and python_version < "4.0"
|
||||
async-generator==1.10; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
atomicwrites==1.4.0; python_version >= "3.6" and python_full_version < "3.0.0" and sys_platform == "win32" or sys_platform == "win32" and python_version >= "3.6" and python_full_version >= "3.4.0"
|
||||
attrs==21.2.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
|
||||
backcall==0.2.0; python_version >= "3.7"
|
||||
backports.entry-points-selectable==1.1.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "2.7"
|
||||
black==21.7b0; python_full_version >= "3.6.2"
|
||||
bleach==4.0.0; python_version >= "3.7"
|
||||
censusdata==1.14; python_version >= "2.7"
|
||||
censusdata==1.15; python_version >= "2.7"
|
||||
certifi==2021.5.30; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.7"
|
||||
cffi==1.14.6; implementation_name == "pypy" and python_version >= "3.6"
|
||||
charset-normalizer==2.0.4; python_full_version >= "3.6.0" and python_version >= "3"
|
||||
click-plugins==1.1.1; python_version >= "3.6"
|
||||
click==8.0.1; python_version >= "3.6"
|
||||
cligj==0.7.2; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version < "4" and python_version >= "3.6"
|
||||
colorama==0.4.4; platform_system == "Windows" and python_version >= "3.7" and python_full_version >= "3.6.2" and sys_platform == "win32" and python_version < "4.0" and (python_version >= "3.7" and python_full_version < "3.0.0" and sys_platform == "win32" or sys_platform == "win32" and python_version >= "3.7" and python_full_version >= "3.5.0")
|
||||
configparser==5.0.2; python_version >= "3.6"
|
||||
colorama==0.4.4; python_version >= "3.7" and python_full_version < "3.0.0" and platform_system == "Windows" and sys_platform == "win32" or platform_system == "Windows" and python_version >= "3.7" and python_full_version >= "3.5.0" and sys_platform == "win32"
|
||||
debugpy==1.4.1; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
|
||||
decorator==5.0.9; python_version >= "3.7"
|
||||
defusedxml==0.7.1; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
|
||||
distlib==0.3.2; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
|
||||
dparse==0.5.1; python_version >= "3.5"
|
||||
dynaconf==3.1.4
|
||||
entrypoints==0.3; python_version >= "3.7"
|
||||
et-xmlfile==1.1.0; python_version >= "3.6"
|
||||
filelock==3.0.12; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
|
||||
fiona==1.8.20; python_version >= "3.6"
|
||||
flake8==3.9.2; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
|
||||
geopandas==0.9.0; python_version >= "3.6"
|
||||
idna==3.2; python_version >= "3.5" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.5"
|
||||
importlib-metadata==3.10.1; python_version < "3.8" and python_version >= "3.7" and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.5.0" and python_version < "3.8" and python_version >= "3.6") and python_full_version >= "3.6.2" and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.4.0" and python_version >= "3.6" and python_version < "3.8")
|
||||
iniconfig==1.1.1; python_version >= "3.6"
|
||||
importlib-metadata==3.10.1; python_version < "3.8" and python_version >= "3.7"
|
||||
ipykernel==6.0.3; python_version >= "3.7"
|
||||
ipython-genutils==0.2.0; python_version >= "3.7"
|
||||
ipython==7.26.0; python_version >= "3.7"
|
||||
ipywidgets==7.6.3
|
||||
isort==5.9.3; python_full_version >= "3.6.1" and python_version < "4.0" and python_version >= "3.6"
|
||||
jedi==0.18.0; python_version >= "3.7"
|
||||
jellyfish==0.6.1
|
||||
jinja2==3.0.1; python_version >= "3.7"
|
||||
jsonschema==3.2.0; python_version >= "3.5"
|
||||
jupyter-client==6.2.0; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
|
|
@ -52,74 +40,56 @@ jupyter-nbextensions-configurator==0.4.1
|
|||
jupyter==1.0.0
|
||||
jupyterlab-pygments==0.1.2; python_version >= "3.7"
|
||||
jupyterlab-widgets==1.0.0; python_version >= "3.6"
|
||||
lazy-object-proxy==1.6.0; python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "4.0" or python_version >= "3.6" and python_version < "4.0" and python_full_version >= "3.6.0"
|
||||
liccheck==0.6.2; python_version >= "2.7"
|
||||
lxml==4.6.3; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
|
||||
markupsafe==2.0.1; python_version >= "3.7"
|
||||
matplotlib-inline==0.1.2; python_version >= "3.7"
|
||||
mccabe==0.6.1; python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "4.0" or python_version >= "3.6" and python_version < "4.0" and python_full_version >= "3.5.0"
|
||||
mistune==0.8.4; python_version >= "3.7"
|
||||
munch==2.5.0; python_version >= "3.6"
|
||||
mypy-extensions==0.4.3; python_full_version >= "3.6.2" and python_version >= "3.5"
|
||||
mypy==0.910; python_version >= "3.5"
|
||||
nbclient==0.5.3; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
nbconvert==6.1.0; python_version >= "3.7"
|
||||
nbformat==5.1.3; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
nest-asyncio==1.5.1; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
notebook==6.4.0; python_version >= "3.6"
|
||||
notebook==6.4.2; python_version >= "3.6"
|
||||
numpy==1.21.1; python_version >= "3.7"
|
||||
openpyxl==3.0.7; python_version >= "3.6"
|
||||
packaging==21.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
|
||||
packaging==21.0; python_version >= "3.7"
|
||||
pandas==1.3.1; python_full_version >= "3.7.1"
|
||||
pandocfilters==1.4.3; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.7"
|
||||
parso==0.8.2; python_version >= "3.7"
|
||||
pathspec==0.9.0; python_full_version >= "3.6.2"
|
||||
pexpect==4.8.0; sys_platform != "win32" and python_version >= "3.7"
|
||||
pickleshare==0.7.5; python_version >= "3.7"
|
||||
platformdirs==2.2.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
|
||||
pluggy==0.13.1; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
|
||||
prometheus-client==0.11.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
|
||||
prompt-toolkit==3.0.19; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
ptyprocess==0.7.0; sys_platform != "win32" and python_version >= "3.7" and os_name != "nt"
|
||||
py==1.10.0; python_version >= "3.6" and python_full_version < "3.0.0" and implementation_name == "pypy" or python_full_version >= "3.5.0" and python_version >= "3.6" and implementation_name == "pypy"
|
||||
pycodestyle==2.7.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
|
||||
py==1.10.0; python_version >= "3.6" and python_full_version < "3.0.0" and implementation_name == "pypy" or implementation_name == "pypy" and python_version >= "3.6" and python_full_version >= "3.4.0"
|
||||
pycparser==2.20; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
|
||||
pyflakes==2.3.1; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
|
||||
pygments==2.9.0; python_version >= "3.7"
|
||||
pylint==2.9.6; python_version >= "3.6" and python_version < "4.0"
|
||||
pyparsing==2.4.7; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.6"
|
||||
pypandoc==1.6.3
|
||||
pyparsing==2.4.7; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.7"
|
||||
pyproj==3.1.0; python_version >= "3.7"
|
||||
pyrsistent==0.18.0; python_version >= "3.6"
|
||||
pytest==6.2.4; python_version >= "3.6"
|
||||
python-dateutil==2.8.2; python_full_version >= "3.7.1" and python_version >= "3.7"
|
||||
pytz==2021.1; python_full_version >= "3.7.1" and python_version >= "2.7"
|
||||
pywin32==301; sys_platform == "win32" and python_version >= "3.6"
|
||||
pywinpty==1.1.3; os_name == "nt" and python_version >= "3.6"
|
||||
pyyaml==5.4.1; python_version >= "3.5" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.5"
|
||||
pyzmq==22.2.0; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
pyyaml==5.4.1; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0"
|
||||
pyzmq==22.2.1; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
qtconsole==5.1.1; python_version >= "3.6"
|
||||
qtpy==1.9.0; python_version >= "3.6"
|
||||
regex==2021.8.3; python_full_version >= "3.6.2"
|
||||
requests==2.26.0; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.6.0")
|
||||
safety==1.10.3; python_version >= "3.5"
|
||||
semantic-version==2.8.5; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "2.7"
|
||||
send2trash==1.7.1; python_version >= "3.6"
|
||||
send2trash==1.8.0; python_version >= "3.6"
|
||||
shapely==1.7.1; python_version >= "3.6"
|
||||
six==1.16.0; python_full_version >= "3.7.1" and python_version >= "3.6" and (python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0") and (python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.6") and (python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.7") and (python_version >= "3.5" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.5")
|
||||
six==1.16.0; python_full_version >= "3.7.1" and python_version >= "3.6" and (python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.6") and (python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.7") and (python_version >= "3.5" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.5")
|
||||
terminado==0.10.1; python_version >= "3.6"
|
||||
testpath==0.5.0; python_version >= "3.7"
|
||||
toml==0.10.2; python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "4.0" or python_full_version >= "3.5.0" and python_version >= "3.6" and python_version < "4.0"
|
||||
tomli==1.2.0; python_version >= "3.6" and python_full_version >= "3.6.2"
|
||||
tornado==6.1; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
tox==3.24.1; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
|
||||
tqdm==4.62.0; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.4.0")
|
||||
traitlets==5.0.5; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
typed-ast==1.4.3; python_version < "3.8" and python_full_version >= "3.6.2" and python_version >= "3.6" and implementation_name == "cpython"
|
||||
types-requests==2.25.2
|
||||
typing-extensions==3.10.0.0; python_version < "3.8" and python_full_version >= "3.6.2" and python_version >= "3.6"
|
||||
types-requests==2.25.6
|
||||
typing-extensions==3.10.0.0; python_version < "3.8" and python_version >= "3.6"
|
||||
urllib3==1.26.6; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version < "4" and python_version >= "2.7"
|
||||
virtualenv==20.7.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
|
||||
us==2.0.2
|
||||
wcwidth==0.2.5; python_full_version >= "3.6.1" and python_version >= "3.7"
|
||||
webencodings==0.5.1; python_version >= "3.7"
|
||||
widgetsnbextension==3.5.1
|
||||
wrapt==1.12.1; python_version >= "3.6" and python_version < "4.0"
|
||||
xlsxwriter==2.0.0
|
||||
zipp==3.5.0; python_version < "3.8" and python_version >= "3.6"
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue