Let’s learn some useful Python Pandas features that you can apply for real bussiness tasks considering Data analysis.

In this video tutorial I will use Python Jupyter Notebook framework which is good for manipulating data with Pandas.

The content of the video:
1: 0:08 - create a Pandas DataFrame
2: 2:03 - take index names and column names into consideration
3: 3:02 - show only part of the data for only one subset
4: 3:20 - reordering data, expand all data by keys one by one.
5: 3:55 - sort by level 1
6. 4:28 - summary statistics by level and key (sum by key 2)
7. 5:08 - summary statistics by level and axis.
8. Learn what is indexes and levels (keys) in Panda DataFrames.

At steps no. 7 and 8 Pandas sum rows by delivered keys and indexes at the level set by user.

During the video I try to explain and show in practise what levels, axis values and indexes are and how to determine them in Pandas Dataframe.

By knowing these Python Pandas tips you can easily slicing dataframes, implement more complicated sorting of data, create data subsets and much more.

Numpy was used only for generate random values to Pandas dataframe.

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#python #jupyter