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The pandas.DataFrame.isin(values) function checks whether each element in the caller DataFrame contains valuesthe value specified in the input .

pandas.DataFrame.isin(values)grammar

DataFrame.isin(values)

parameter

Return Value

DataFrameIt returns a boolean value of the same dimension as the caller DataFrame, indicating whether each element contains the input values.

Sample code: DataFrame.isin()Taking Iterableas input

When Python iterableis given as input, the Pandas DataFrame.isin()function checks DataFramewhether each value in contains iterableany of the values ​​in .

import pandas as pd

df = pd.DataFrame({'Sales': [100, 200], 'Profit': [200, 400]})

df = df.isin([200, 400])
print(df)

The caller DataFrameis

   Sales  Profit
0    100     200
1    200     400

Output:

   Sales  Profit
0  False    True
1   True    True

Here, 200 and 400 are present [200，400]in the list , so in the returned DataFrame, the original values ​​are 200 and 400. Trueis 100not in the list [200，400], so the value in its place is returned False.

Example code: DataFrame.isin()Taking a dictionary as input

If the input value type is dictionary, the function checks not only the value but also the key value. It returns isin()only if the column name is the same as the key and the cell value is contained in the dictionary .valueTrue

import pandas as pd

df = pd.DataFrame({"Sales": [100, 200], "Profit": [200, 400]})

df = df.isin({"Sales": [200, 400]})
print(df)

Output:

   Sales  Profit
0  False   False
1   True   False

In the first example, Profitthe values ​​of the columns are all True, but in this case they are False, because the column names are different than the keys in the input dictionary.

If the value is contained in the dictionary – [200，400]it will return the value Salesin the column True.

Sample code: DataFrame.isin()Taking Seriesas input

If the input value type is Pandas Series, isin()the function checks if each column element is Seriesthe same as the value in the same index of the input .

import pandas as pd

df = pd.DataFrame({"Sales": [100, 200], "Profit": [200, 400]})

valueSeries = pd.Series([200, 400])
print(valueSeries)

df = df.isin(valueSeries)
print(df)

Output:

0    200
1    400
dtype: int64
   Sales  Profit
0  False    True
1  False    True

ProfitThe elements in the column Seriesare the same as the elements in the input , so both elements in the column are returned True.

Sample code: DataFrame.isin()Taking DataFrameas input

If the input value type is Pandas, the function checks whether each element in DataFrame.isin()the caller is the same as the element at the same position in the input.DataFrameDataFrame

Returns if the values ​​are the same True, otherwise returns None False.

import pandas as pd

df = pd.DataFrame({"Sales": [100, 200], "Profit": [200, 400]})
print(df)

valueDf = pd.DataFrame({"Sales": [100, 200], "Profit": [200, 300]})
print(valueDf)

df = df.isin(valueDf)
print(df)

Output:

   Sales  Profit
0    100     200
1    200     400
   Sales  Profit
0    100     200
1    200     300
   Sales  Profit
0   True    True
1   True   False

(1, 1)The value of position is returned Falsebecause the values ​​of the caller DataFrame and the input DataFrame are different.