Interview Questions and Answers

Example:

df = pd.DataFrame({'column1': [1, 2, 3], 'column2': ['a', 'b', 'c']})

Example:

df.to_csv('output.csv', index=False)

Example:

df = pd.read_csv('file.csv')

Example:

df.describe()

Example:

df['date_column'] = pd.to_datetime(df['date_column'])

Example:

df.nlargest(5, 'column')

Example:

df.to_excel('output.xlsx', index=False)

Example:

df.groupby('column1').mean()

Example:

pd.merge(df1, df2, on='common_column')

Example:

pd.melt(df, id_vars=['id_column'], value_vars=['value_column'])

Example:

pd.concat([df1, df2], axis=1)

Example:

df['column'].nunique()

Example:

pd.cut(df['column'], bins=[0, 25, 50, 75, 100])

Example:

df.dropna().mean()

Example:

for index, row in df.iterrows():
    print(index, row['column'])

Example:

pd.get_dummies(df['column'])

Example:

df['column'] = pd.to_numeric(df['column'], errors='coerce')

Example:

pd.cut(df['column'], bins=[0, 25, 50, 75, 100])

Example:

df.pivot(index='index_column', columns='column_to_pivot', values='value_column')

Example:

pd.crosstab(df['factor1'], df['factor2'])

Example:

df.dropna().mean()

Example:

pd.pivot_table(df, values='value', index='index_column', columns='column_to_pivot')

Example:

df['normalized_column'] = df.groupby('group_column')['value_column'].transform(lambda x: (x - x.mean()) / x.std())

Example:

df.pipe(my_function).dropna()

Example:

df.stack()