pandas-should
pandas-should is pandas extension for asserting.
Install
Install and update released version using pip:
$ pip install pandas-shouldIf you want development version:
$ pip install git+https://github.com/momijiame/pandas-should.gitQuickstart
You can just to import pandas_should to use:
import pandas_shouldDataFrame
Length (rows)
Before:
assert len(df1) == len(df2)After:
assert df1.should.have_same_length(df2)Or
assert df1.should.have_length(len(df2))Before (multiple DataFrame):
assert len(df1) == (len(df2) + len(df3))After (multiple DataFrame)
assert df1.should.have_same_length(df2, df3)Width (columns)
Before:
assert len(df1.columns) == len(df2.columns)After:
assert df1.should.have_same_width(df2)Or
assert df1.should.have_width(len(df2.columns))Before (multiple DataFrame):
assert len(df1.columns) == (len(df2.columns)) + len(df3.columns)))After (multiple DataFrame)
assert df1.should.have_same_width(df2, df3)Equality
Before:
from pandas.util.testing import assert_frame_equal
def equal(a, b):
try:
assert_frame_equal(a, b)
except AssertionError:
return False
return True
assert equal(df1, df2)After:
assert df1.should.equal(df2)Null inclusion
Before:
assert df.isnull().any(axis=None)After:
assert df.should.have_null()Or expect not to be included:
assert df.should.have_not_null()
assert not df.should.have_null()Shape
Before:
assert df1.shape == df2.shapeAfter:
assert df1.should.be_shaped_like(df2)Or
assert df1.should.be_shaped_like(df2.shape)
assert df1.should.be_shaped_like(df2.shape[0], df2.shape[1])Value range
Before:
assert (df >= range_min).any(axis=None) and (df <= range_max).any(axis=None) After:
assert df.should.fall_within_range(range_min, range_max)Greater than only:
assert df.should.greater_than(range_min)
assert df.should.greater_than_or_equal(range_min)Less than only:
assert df.should.less_than(range_min)
assert df.should.less_than_or_equal(range_min)Series
Length
Before:
assert len(s1) == len(s2)After:
assert s1.should.have_same_length(s2)Or:
assert s1.should.have_length(len(s2))Before (multiple Series):
assert len(s1) == (len(s2) + len(s3))After (multiple Series):
assert s1.should.have_same_length(s2, s3)Equality
Before:
from pandas.util.testing import assert_series_equal
def equal(a, b):
try:
assert_series_equal(a, b)
except AssertionError:
return False
return True
assert equal(s1, s2)After:
assert s1.should.equal(s2)Null inclusion
Before:
assert s.isnull().any()After:
assert s.should.have_null()Or expect not to be included:
assert s.should.have_not_null()
assert not s.should.have_null()Value range
Before:
assert (s >= range_min).any() and (s <= range_max).any() After:
assert s.should.fall_within_range(range_min, range_max)Greater than only:
assert s.should.greater_than(range_min)
assert s.should.greater_than_or_equal(range_min)Less than only:
assert s.should.less_than(range_min)
assert s.should.less_than_or_equal(range_min)Value variety
Before:
assert len(s.unique()) == expect_sizeAfter:
assert s.should.have_number_of_unique_values(expect_size)
