Data Manipulation & Analysis Using Python (Pandas & Matplotlib) (English) | Pandas library

Outlines:
1) Load the Pandas library and check the panda's library version
2) Read/Load the data: '.csv file' (comma-separated values file)
3) Save the dataset to a variable
4) import the Python library (such as Pandas) with an alias
5) Python Library: Pandas Functions and Attributes
6) Subsetting data
i) Accessing the particular column(s) from the data set
ii) Accessing the names of the columns in the data sets (Variable names)
iii) Delete columns (Variables)
iv) Checking Rows wise data: Using Method "loc and iloc"
7) Grouped and Aggregated Calculations
i) Use of 'groupby' function
8) Different Ways of writing the code
9) Categorical Data Analysis and Visualization
i) Pandas and Matlibplot library
10) Use of Pivot Tables
11) Quantitative Data Visualization
#DataManipulation #DataVisualization #Python #Pandas #MatlibPlot

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