pandas.Series.compare — pandas 2.2.3 documentation (original) (raw)

Series.compare(other, align_axis=1, keep_shape=False, keep_equal=False, result_names=('self', 'other'))[source]#

Compare to another Series and show the differences.

Parameters:

otherSeries

Object to compare with.

align_axis{0 or ‘index’, 1 or ‘columns’}, default 1

Determine which axis to align the comparison on.

• 0, or ‘index’Resulting differences are stacked vertically
  with rows drawn alternately from self and other.
• 1, or ‘columns’Resulting differences are aligned horizontally
  with columns drawn alternately from self and other.

keep_shapebool, default False

If true, all rows and columns are kept. Otherwise, only the ones with different values are kept.

keep_equalbool, default False

If true, the result keeps values that are equal. Otherwise, equal values are shown as NaNs.

result_namestuple, default (‘self’, ‘other’)

Set the dataframes names in the comparison.

Added in version 1.5.0.

Returns:

Series or DataFrame

If axis is 0 or ‘index’ the result will be a Series. The resulting index will be a MultiIndex with ‘self’ and ‘other’ stacked alternately at the inner level.

If axis is 1 or ‘columns’ the result will be a DataFrame. It will have two columns namely ‘self’ and ‘other’.

Notes

Matching NaNs will not appear as a difference.

Examples

s1 = pd.Series(["a", "b", "c", "d", "e"]) s2 = pd.Series(["a", "a", "c", "b", "e"])

Align the differences on columns

s1.compare(s2) self other 1 b a 3 d b

Stack the differences on indices

s1.compare(s2, align_axis=0) 1 self b other a 3 self d other b dtype: object

Keep all original rows

s1.compare(s2, keep_shape=True) self other 0 NaN NaN 1 b a 2 NaN NaN 3 d b 4 NaN NaN

Keep all original rows and also all original values

s1.compare(s2, keep_shape=True, keep_equal=True) self other 0 a a 1 b a 2 c c 3 d b 4 e e