Python

df.isna().sum()

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

null_cols = df.columns[df.isnull().all()]
df.drop(null_cols, axis = 1, inplace = True)

df = df[df.columns[~df.isnull().all()]]

dfObj.isnull().sum()

df.isna()

dataframe.isnull()
dataframe.any()

dfObj.isnull().sum().sum()

# Count the number of Missing Values in the DataFrame
df.isna().sum()

# Count the number of Non-Missing Values in the DataFrame
df.count()

cols_to_delete = df.columns[df.isnull().sum()/len(df) > .90]
df.drop(cols_to_delete, axis = 1, inplace = True)

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