The correct answer is C. Cross-tabulation of categorical data.
A crosstab, also known as a contingency table or cross tabulation, is a summary table that displays the frequency distribution of two or more variables in a single table. It is a powerful tool for exploring the relationships between variables and for identifying patterns in data.
The crosstab function in Pandas is used to create crosstabs of categorical data. It takes two or more DataFrame objects as input and returns a DataFrame object with one row for each unique combination of values in the input DataFrame objects. The columns of the output DataFrame object correspond to the values of the categorical variables.
For example, if you have a DataFrame object with columns “Gender” and “Age”, you can use the crosstab function to create a crosstab of these two variables. The output DataFrame object will have one row for each unique combination of gender and age, and the columns of the output DataFrame object will correspond to the values of the two categorical variables.
The crosstab function is a powerful tool for exploring the relationships between categorical variables. It can be used to identify patterns in data, to compare the distribution of values across different groups, and to test hypotheses about the relationships between variables.
The other options are incorrect because they do not describe the primary purpose of the crosstab function in Pandas.
- Option A is incorrect because the crosstab function is not primarily used for data transformation. Data transformation is the process of changing the format or structure of data. The crosstab function does not change the format or structure of data.
- Option B is incorrect because the crosstab function is not primarily used for data visualization. Data visualization is the process of creating graphical representations of data. The crosstab function does not create graphical representations of data.
- Option D is incorrect because the crosstab function is not primarily used for data cleaning and preprocessing. Data cleaning and preprocessing are the processes of identifying and correcting errors in data and preparing data for analysis. The crosstab function does not identify and correct errors in data or prepare data for analysis.