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We will look at methods for counting the number of NaN occurrences in a column of a Pandas DataFrame. We have a number of options, including isna()the method for one or more columns, by NaNsubtracting the total length from the number of occurrences, using value_countsthe method, and using df.isnull().sum()the method.

We will also introduce methods to count the total number of occurrences in an entire Pandas DataFrame NaN.

isna()Method to count NaNs in one or more columns

We can use insna()the method (Pandas version > 0.21.0) and then sum to count NaNthe occurrences of . For one column, we would do the following:

import pandas as pd

s = pd.Series([1, 2, 3, np.nan, np.nan])
s.isna().sum()
# or s.isnull().sum() for older pandas versions

Output:

2

For several columns it also works:

import pandas as pd

df = pd.DataFrame({"a": [1, 2, np.nan], "b": [np.nan, 1, np.nan]})
df.isna().sum()

Output:

a    1
b    2
dtype: int64

Subtract the count of from the total length non-NaNto calculate NaNthe number of occurrences of

NaNWe can get the number of occurrences of in each column by subtracting the number of non-occurrences from the length of the dataframe NaN:

import pandas as pd

df = pd.DataFrame(
    [(1, 2, None), (None, 4, None), (5, None, 7), (5, None, None)],
    columns=["a", "b", "d"],
    index=["A", "B", "C", "D"],
)
print(df)
print(len(df) - df.count())

Output:

     a    b    d
A  1.0  2.0  NaN
B  NaN  4.0  NaN
C  5.0  NaN  7.0
D  5.0  NaN  NaN
a    1
b    2
d    3
dtype: int64

df.isnull().sum()Method to count NaNthe number of occurrences of

We can df.isnull().sum()get NaNthe number of occurrences of in each column using the method. If we sumpass in the method axis=0, it will give the number of occurrences of in each column NaN. If we need to have occurrences of in each row NaN, we need to set axis=1.

Consider the following code:

import pandas as pd

df = pd.DataFrame(
    [(1, 2, None), (None, 4, None), (5, None, 7), (5, None, None)],
    columns=["a", "b", "d"],
    index=["A", "B", "C", "D"],
)

print("NaN occurrences in Columns:")
print(df.isnull().sum(axis=0))
print("NaN occurrences in Rows:")
print(df.isnull().sum(axis=1))

Output:

NaN occurrences in Columns:
a    1
b    2
d    3
dtype: int64
NaN occurrences in Rows:
A    1
B    2
C    1
D    2
dtype: int64

Count NaNthe occurrences of in the entire Pandas DataFrame

To get the total number of DataFrameall NaNoccurrences of in , we .sum()chain two methods together:

import pandas as pd

df = pd.DataFrame(
    [(1, 2, None), (None, 4, None), (5, None, 7), (5, None, None)],
    columns=["a", "b", "d"],
    index=["A", "B", "C", "D"],
)

print("NaN occurrences in DataFrame:")
print(df.isnull().sum().sum())

Output:

NaN occurrences in DataFrame:
6