This code sample is a walkthrough to cover the fundamental concepts to use for Python Pandas used in Data Science.
Here, we then look at different ways I tried to perform on Pokemon Dataset:
- Loading the data into Pandas (CSVs, Excel, TXTs, etc.)
- Reading Data (Getting Rows, Columns, Cells, Headers, etc.)
- Iterate through each Row
- Getting rows based on a specific condition
- High Level description of your data (min, max, mean, std dev, etc.)
- Sorting Values (Alphabetically, Numerically)
- Making Changes to the DataFrame
- Adding a column
- Deleting a column
- Summing Multiple Columns to Create new Column.
- Rearranging columns
- Saving our Data (CSV, Excel, TXT, etc.)
- Filtering Data (based on multiple conditions)
- Reset Index
- Regex Filtering (filter based on textual patterns)
- Conditional Changes
- Aggregate Statistics using Groupby (Sum, Mean, Counting)
- Working with large amounts of data (setting chunksize)