pandas.Series.compare#

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’.

See also

DataFrame.compare

Compare with another DataFrame and show differences.

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 other1    b     a3    d     b

Stack the differences on indices

>>>s1.compare(s2,align_axis=0)1  self     b   other    a3  self     d   other    bdtype: object

Keep all original rows

>>>s1.compare(s2,keep_shape=True)  self other0  NaN   NaN1    b     a2  NaN   NaN3    d     b4  NaN   NaN

Keep all original rows and also all original values

>>>s1.compare(s2,keep_shape=True,keep_equal=True)  self other0    a     a1    b     a2    c     c3    d     b4    e     e