The scope of pandas is so broad that it is easier to list the functions that it cannot handle.
The library is a comfortable place where you can do anything with your data: morocco rcs data collect, clean, transform and analyze.
Let's say you want to explore a dataset from your computer in CSV format. Using Pandas, the information will be extracted from the CSV into a DataFrame, i.e. presented as a table, and then you can:
Calculate statistics and get answers to the following questions:
What is the mean, median, maximum, or minimum for each column?
Is column A correlated with column B?
What does the distribution of data in column C look like?
Perform data cleanup, including removing missing values or filtering rows or columns based on specified criteria.
Visualize data using Matplotlib by plotting bar charts, line graphs, or histograms.
Save cleaned and transformed data to CSV and other file formats or to a database.
Рandas is the best tool to understand the nature of your data set. Once you do that, modeling it or creating complex visualizations is a breeze.
What is the pandas library for?
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