Pandas DataFrame isin() Method.
Table Of Contents:
- Syntax isin( ) Method.
- Examples isin( ) Method.
(1) Syntax:
DataFrame.isin(values)Description:
- The
isin()method checks if the Dataframe contains the specified value(s). - It returns a DataFrame similar to the original DataFrame, but the original values have been replaced with
Trueif the value was one of the specified values, otherwiseFalse.
Parameters:
- values: iterable, Series, DataFrame or dict – – The result will only be true at a location if all the labels match. If values is a Series, that’s the index. If values is a dict, the keys must be the column names, which must match. If values is a DataFrame, then both the index and column labels must match.
Returns:
- DataFrame – DataFrame of booleans showing whether each element in the DataFrame is contained in values.
(2) Examples Of items() Method:
Example-1
import pandas as pd
data = {
"name": ["Sally", "Mary", "John"],
"age": [50, 40, 30]
}
df = pd.DataFrame(data)
dfOutput:
df.isin([50, 30])
df[df.isin([50, 30])]Example-2
df = pd.DataFrame({'num_legs': [2, 4], 'num_wings': [2, 0]},
index=['falcon', 'dog'])
dfOutput:
df.isin([0, 2])Output:
To check if values is not in the DataFrame, use the ~ operator:
~df.isin([0, 2])Output:
When values is a dict, we can pass values to check for each column separately:
df.isin({'num_wings': [0, 3]})Output:
When values is a Series or DataFrame the index and column must match. Note that ‘falcon’ does not match based on the number of legs in other.
other = pd.DataFrame({'num_legs': [8, 3], 'num_wings': [0, 2]},
index=['spider', 'falcon'])
df.isin(other)Output:
