#datascience #pandaspythontutorial #pandastricks
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Video Description:
In this video, we'll be discussing some tips and tricks for working with Pandas, the popular Python library for data manipulation and analysis. Whether you're a beginner looking to get started with Pandas or an experienced user looking to up your game, this video has something for you. We'll be covering a range of topics, including:

How to read and write data from different file formats (such as CSV, Excel, and SQL)
How to select and filter data using Pandas' powerful indexing and querying capabilities
How to group and aggregate data using Pandas' groupby function
How to handle missing or incomplete data
And much more!
This tutorial is presented in Urdu/Hindi, so it's perfect for those who are more comfortable learning in these languages. However, even if you don't speak Urdu or Hindi, the visuals and examples in the video should still be easy to follow along with. So if you're interested in learning more about Pandas, be sure to check out this video!---------------------------------------------------------------------------------------------------------------------------------------

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Timestamp:
00:00:00 Agenda
00:00:58 01- Pandas Version?
00:02:58 02- Creating a DataFrame?
00:10:35 03- Columns Renames?
00:19:22 04- Template Data?
00:25:55 05- Own Data?
00:28:00 Assignment
00:28:22 06- Reverse Row Order
00:32:05 07- Reverse Column Order
00:33:03 08- Select a column by dtype
00:36:57 09- Convert Strings to Number
00:43:25 10- Reduce DataFrame Size
00:47:23 11- Copy Data From Clipboard
00:53:20 12- Split the DataFrame
00:57:28 13- Join two Datasets
00:58:47 14- Filtering a Dataset
01:08:53 Assignment
01:10:14 15- Filtering by Large Categories
01:15:30 16- Spliting a string into Multiple Column
01:24:33 17- Aggregate by multiple group/function
01:31:08 18- Select Specific Rows or Column
01:37:03 19- Reshape Multi Index Series
01:41:08 20- Continous to Categorical data Conversion
01:45:00 21- Convert one Set of values into another one
01:50:06 22- Transpose a wide dataframe
01:54:16 23- Reshaping a data frame