Motivation

The goal of this file is to demonstrate the capabilities of Pretty Jupyter package.

Input Data

In this section, we inspect the input data.

	money	weight	gender
0	30000	80	Male
1	40000	50	Female
2	70000	80	Male
3	65000	70	Male
4	25000	54	Female

The input dataset has:

• 5 rows,
• 3 columns.

The columns and their dtypes are the following:

	col_name	dtype
0	money	int64
1	weight	int64
2	gender	object

Money

Gender

C:\Users\janpa\AppData\Local\Temp\ipykernel_16720\2606098142.py:3: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.
  ax.figure.show()

Weight

Weight is a continuous variable.

Correlations

Correlation between the money and weight seems to be rather weak. The gender is not analyzed because it's a categorical variable.

Conclusion

Pretty Jupyter is awesome and I'm definitely installing it ;).