Answers for "count nan values pandas"

dataframe find nan rows

df[df.isnull().any(axis=1)]

count nan pandas

#Python, pandas
#Count missing values for each column of the dataframe df

df.isnull().sum()

find position of nan pandas

# position of NaN values in terms of index
df.loc[pandas.isna(df["b"]), :].index

# position of NaN values in terms of rows that cotnain NaN
df.loc[pandas.isna(df["b"]), :]

check if a value in dataframe is nan

#return a subset of the dataframe where the column name value == NaN 
df.loc[df['column name'].isnull() == True]

df count missing values

In [5]: df = pd.DataFrame({'a':[1,2,np.nan], 'b':[np.nan,1,np.nan]})

In [6]: df.isna().sum()
Out[6]:
a    1
b    2
dtype: int64

to detect if a data frame has nan values

df.isnull().sum().sum()
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