Pandas Questions et reponses d'entretien

Question 21. Explain the purpose of the crosstab() function in Pandas.

crosstab() computes a cross-tabulation of two or more factors.

Example:

pd.crosstab(df['Factor1'], df['Factor2'])

Question 22. How to handle categorical data in Pandas?

You can use the astype() method to convert a column to a categorical type: df['Category'] = df['Category'].astype('category')

Question 23. Explain the use of melt() function in Pandas.

melt() is used to reshape or transform data by unpivoting it.

Example:

pd.melt(df, id_vars=['ID'], value_vars=['Var1', 'Var2'])

Question 24. What is the purpose of the to_csv() method in Pandas?

to_csv() is used to write a DataFrame to a CSV file.

Example:

df.to_csv('output.csv', index=False)

Question 25. Explain the use of the nunique() function in Pandas.

nunique() returns the number of unique elements in a column.

Example:

df['Column'].nunique()