Quick fix: updating snapshots to have more sigfigs (#1409)

Updated snapshots to include 10 digits after the decimal
This commit is contained in:
Emma Nechamkin 2022-03-14 21:44:35 -04:00 committed by GitHub
commit 2279a04c94
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GPG key ID: 4AEE18F83AFDEB23
7 changed files with 214 additions and 213 deletions

View file

@ -1,16 +1,16 @@
GEOID10_TRACT,Input Field 1
06007040300,2.00000
06001020100,6.10000
06007040500,-7.80000
15001021010,12.00000
15001021101,12.05525
15007040603,13.51418
15007040700,13.11989
15009030100,13.60947
15009030201,13.73235
15001021402,14.73305
15001021800,16.60834
15009030402,16.00254
15009030800,15.34818
15003010201,14.58789
15007040604,14.27705
06007040300,2.0000000000
06001020100,6.1000000000
06007040500,-7.8000000000
15001021010,12.0000000000
15001021101,12.0552478300
15007040603,13.5141757800
15007040700,13.1198897600
15009030100,13.6094698300
15009030201,13.7323516400
15001021402,14.7330511600
15001021800,16.6083385700
15009030402,16.0025350000
15009030800,15.3481825100
15003010201,14.5878876900
15007040604,14.2770491700

1 GEOID10_TRACT Input Field 1
2 06007040300 2.00000 2.0000000000
3 06001020100 6.10000 6.1000000000
4 06007040500 -7.80000 -7.8000000000
5 15001021010 12.00000 12.0000000000
6 15001021101 12.05525 12.0552478300
7 15007040603 13.51418 13.5141757800
8 15007040700 13.11989 13.1198897600
9 15009030100 13.60947 13.6094698300
10 15009030201 13.73235 13.7323516400
11 15001021402 14.73305 14.7330511600
12 15001021800 16.60834 16.6083385700
13 15009030402 16.00254 16.0025350000
14 15009030800 15.34818 15.3481825100
15 15003010201 14.58789 14.5878876900
16 15007040604 14.27705 14.2770491700

View file

@ -1,16 +1,16 @@
GEOID10_TRACT,Example Field 1
06007040300,4.00000
06001020100,12.20000
06007040500,-15.60000
15001021010,24.00000
15001021101,24.11050
15007040603,27.02835
15007040700,26.23978
15009030100,27.21894
15009030201,27.46470
15001021402,29.46610
15001021800,33.21668
15009030402,32.00507
15009030800,30.69637
15003010201,29.17578
15007040604,28.55410
06007040300,4.0000000000
06001020100,12.2000000000
06007040500,-15.6000000000
15001021010,24.0000000000
15001021101,24.1104956600
15007040603,27.0283515600
15007040700,26.2397795200
15009030100,27.2189396600
15009030201,27.4647032800
15001021402,29.4661023200
15001021800,33.2166771400
15009030402,32.0050700000
15009030800,30.6963650200
15003010201,29.1757753800
15007040604,28.5540983400

1 GEOID10_TRACT Example Field 1
2 06007040300 4.00000 4.0000000000
3 06001020100 12.20000 12.2000000000
4 06007040500 -15.60000 -15.6000000000
5 15001021010 24.00000 24.0000000000
6 15001021101 24.11050 24.1104956600
7 15007040603 27.02835 27.0283515600
8 15007040700 26.23978 26.2397795200
9 15009030100 27.21894 27.2189396600
10 15009030201 27.46470 27.4647032800
11 15001021402 29.46610 29.4661023200
12 15001021800 33.21668 33.2166771400
13 15009030402 32.00507 32.0050700000
14 15009030800 30.69637 30.6963650200
15 15003010201 29.17578 29.1757753800
16 15007040604 28.55410 28.5540983400

View file

@ -1,16 +1,16 @@
GEOID10_TRACT,Input Field 1,Example Field 1
06007040300,2.00000,4.00000
06001020100,6.10000,12.20000
06007040500,-7.80000,-15.60000
15001021010,12.00000,24.00000
15001021101,12.05525,24.11050
15007040603,13.51418,27.02835
15007040700,13.11989,26.23978
15009030100,13.60947,27.21894
15009030201,13.73235,27.46470
15001021402,14.73305,29.46610
15001021800,16.60834,33.21668
15009030402,16.00254,32.00507
15009030800,15.34818,30.69637
15003010201,14.58789,29.17578
15007040604,14.27705,28.55410
06007040300,2.0000000000,4.0000000000
06001020100,6.1000000000,12.2000000000
06007040500,-7.8000000000,-15.6000000000
15001021010,12.0000000000,24.0000000000
15001021101,12.0552478300,24.1104956600
15007040603,13.5141757800,27.0283515600
15007040700,13.1198897600,26.2397795200
15009030100,13.6094698300,27.2189396600
15009030201,13.7323516400,27.4647032800
15001021402,14.7330511600,29.4661023200
15001021800,16.6083385700,33.2166771400
15009030402,16.0025350000,32.0050700000
15009030800,15.3481825100,30.6963650200
15003010201,14.5878876900,29.1757753800
15007040604,14.2770491700,28.5540983400

1 GEOID10_TRACT Input Field 1 Example Field 1
2 06007040300 2.00000 2.0000000000 4.00000 4.0000000000
3 06001020100 6.10000 6.1000000000 12.20000 12.2000000000
4 06007040500 -7.80000 -7.8000000000 -15.60000 -15.6000000000
5 15001021010 12.00000 12.0000000000 24.00000 24.0000000000
6 15001021101 12.05525 12.0552478300 24.11050 24.1104956600
7 15007040603 13.51418 13.5141757800 27.02835 27.0283515600
8 15007040700 13.11989 13.1198897600 26.23978 26.2397795200
9 15009030100 13.60947 13.6094698300 27.21894 27.2189396600
10 15009030201 13.73235 13.7323516400 27.46470 27.4647032800
11 15001021402 14.73305 14.7330511600 29.46610 29.4661023200
12 15001021800 16.60834 16.6083385700 33.21668 33.2166771400
13 15009030402 16.00254 16.0025350000 32.00507 32.0050700000
14 15009030800 15.34818 15.3481825100 30.69637 30.6963650200
15 15003010201 14.58789 14.5878876900 29.17578 29.1757753800
16 15007040604 14.27705 14.2770491700 28.55410 28.5540983400

View file

@ -33,6 +33,7 @@ class TestETL:
_EXTRACT_CSV_FILE_NAME = "extract.csv"
_TRANSFORM_CSV_FILE_NAME = "transform.csv"
_OUTPUT_CSV_FILE_NAME = "output.csv"
_FLOAT_FORMAT = "%.10f"
# This *does* need to be updated in the child class. It specifies where the "sample data" is
# so that we do not have to manually copy the "sample data" when we run the tests.
@ -229,7 +230,7 @@ class TestETL:
)
snapshot.snapshot_dir = self._DATA_DIRECTORY_FOR_TEST
snapshot.assert_match(
tmp_df.to_csv(index=False, float_format="%.5f"),
tmp_df.to_csv(index=False, float_format=self._FLOAT_FORMAT),
self._EXTRACT_CSV_FILE_NAME,
)
@ -243,7 +244,7 @@ class TestETL:
snapshot.snapshot_dir = self._DATA_DIRECTORY_FOR_TEST
snapshot.assert_match(
etl.output_df.to_csv(index=False, float_format="%.5f"),
etl.output_df.to_csv(index=False, float_format=self._FLOAT_FORMAT),
self._TRANSFORM_CSV_FILE_NAME,
)
@ -297,7 +298,7 @@ class TestETL:
# Check the snapshots
snapshot.snapshot_dir = self._DATA_DIRECTORY_FOR_TEST
snapshot.assert_match(
actual_output.to_csv(index=False, float_format="%.5f"),
actual_output.to_csv(index=False, float_format=self._FLOAT_FORMAT),
self._OUTPUT_CSV_FILE_NAME,
)