CODEWITHSUNDEEP
pythonpandaspytestassertassertion
EverydayLearner
EverydayLearner

Reputation: 59

How to use assert_frame_equal() for asserting all the values in the dataframe without exiting on failure

I am a newbie to python and dataframes. I am currently trying to compare 2 dataframes with the assert_frame_equal() function .

df1=     a  b
      0  1  3
      1  2  4

df2=    a   b
      0  2  3.0
      1  2  4.0

code:

import pandas as pd
from pandas._testing import assert_frame_equal
def test_compare_src_trg():
 df1 = pd.DataFrame({'a': [1, 2], 'b': [3, 4]})
 df2 = pd.DataFrame({'a': [2, 2], 'b': [3.0, 4.0]})
 pd.testing.assert_frame_equal(df1, df2)

When this is run , the assertion fails at the first column as value "1" is not equal "2" which is correct. But I want the assertion to run on all items of dataframe and give the overall pass/fail results .

----------------------------------
raise AssertionError(msg)
AssertionError: DataFrame.iloc[:, 0] (column name="a") are different

DataFrame.iloc[:, 0] (column name="a") values are different (50.0 %)
[index]: [0, 1]
[left]:  [1, 2]
[right]: [2, 2]

Process finished with exit code 1

Upvotes: 1

Views: 3268

Answers (1)

Romain
Romain

Reputation: 21898

I think you have to use something else like compare. You can see the full comparison and assert if the resulting Dataframe is empty to check if they are equal.

cp = df1.compare(df2)
#      a
#   self other
# 0  1.0   2.0

assert cp.empty, "Dataframes are not equal"
# AssertionError: Dataframes are not equal

Note

Can only compare identically-labeled (i.e. same shape, identical row and column labels) DataFrames

Upvotes: 1

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