pandas.DataFrame.isna¶

Detect missing values.

Return a boolean same-sized object indicating if the values are NA. NA values, such as None or numpy.NaN, gets mapped to True values. Everything else gets mapped to False values. Characters such as empty strings '' or numpy.inf are not considered NA values (unless you set pandas.options.mode.use_inf_as_na = True).

return: DataFrame Mask of bool values for each element in DataFrame that indicates whether an element is not an NA value.

Examples¶

Detect missing values.¶

import pandas as pd
import numpy as np
from numba import njit


@njit
def dataframe_isna():
    df = pd.DataFrame({'A': [1.0, np.nan, 3.0, 1.0], 'B': [4, 5, 6, 7], 'C': [None, 'b', 'c', 'd']})

    return df.isna()


print(dataframe_isna())

$ python ./dataframe/dataframe_isna.py
       A      B      C
0  False  False   True
1   True  False  False
2  False  False  False
3  False  False  False

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pandas.DataFrame.isna¶

Examples¶