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df.dropna(how='all')
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# Drop rows that contain missing data and update the DataFrame.
data = data.dropna(axis=0)
# Confirm the data contains no missing values.
data.isnull().sum(axis=0)
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# Drop only rows from the dataframe where value of column A is missing
# Other rows will remain even if other columns have missing values as long as column A has no missing value
df.dropna(subset=['A'], inplace=True)