Pandas is the most useful data analysis package in Python. You can use it to clean-up, transform and analyze data. Recently, I had a chance to use Pandas for some work. So, in this video let me share a quick but fairly in-depth introduction to Pandas with a real-world case study.
SAMPLE FILES & INSTRUCTIONS:
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~ i n s t a l l a t i o n ~
Download and install Pandas & other data analysis packages:
- from Anaconda
- from Pandas website
- from VS Code
~ s a m p l e f i l e ~
- Direct Download
- On Kaggle
~ c o d e ~
- Jupyter Notebook
- Kaggle Notebook
⏱ VIDEO CHAPTERS
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0:00 - What is Pandas for Python?
0:55 - About the sample data & getting started
2:17 - Importing the libraries and loading data to data frame
4:08 - Fixing the data frame delimiter issue
5:21 - Using basic pandas functions (describe etc.)
7:15 - Fixing the text data issue by removing them
8:35 - Solving the problem correctly
11:20 - Adding a column with IF this then that type rule
13:38 - Filling the text value up (using fillna method)
16:13 - Removing the unnecessary rows
16:37 - Doing quick analysis of data (tables & graphs)
LEARN MORE ABOUT PYTHON
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Watch my 1-hour Python Tutorial to understand and write your first programs -
️ Other ways to clean this data
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We can also use Power Query in Excel to cleanse and process this data. See this tutorial for that -
LEARN MORE ABOUT PANDAS
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Data Science with Pandas - Tutorial on VSCODE page -
Pandas documentation & examples -
Pandas books:
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython by Wes McKinney -
Pandas Cookbook by Daniel Chen -
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What do pandas use to record their thoughts?
Notebooks of course