Together with Matplotlib and NumPy, Pandas complete the trifecta of packages any data analyst need to know to perform data analysis.
Pandas offer a wider range of tools to derive insights and create new features in the dataset at hand.
In this video, well, learn
00:11 - Introduction
00:59 - Creation of Empty DataFrame and Series
02:38 - Create a DataFrame Through Lists
04:24 - Create a DataFrame Through Dictionaries
05:53 - Create a DataFrame Through Series
08:47 - Create a DataFrame Through Tuples
10:47 - Renaming the Columns
11:24 - Reading File Through CSVs
15:35 - Basic DataFrame Inspection
18:52 - Slicing the DataFrame and Rearranging Columns
25:39 - Understanding Index (Indices in Python)
26:23 - Index Methods (Setting, Resetting)
32:22 - Creation of New Columns
37:45 - Df.replace() method
42:55 - Df. Apply()
44:46 - Changing the Data Type of a Column (df.astype())
46:30 - The Basics of Merge
49:48 - Merging the DataFrames
51:30 - Concatenating DataFrames using the pd.concat()
54:53 - Basic Descriptive Stats in Pandas
56:45 - Aggregations Using df.groupby() method
1:01:01 - Sort Values
Stay tuned for more advanced methods, techniques, and packages!
