A Step-by-Step Data Cleaning in Python: Removing Duplicates, Nulls & Visualizing Data. Master Data Cleaning with Python Pandas: CSV File to Visualization in Jupyter Notebook.
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In this video, I’ll show you how to clean data using Python, Pandas, and Jupyter Notebook. We'll start by loading a CSV file, then tackle common data issues like duplicates and missing values. I'll also guide you through dropping unnecessary data and creating visualizations such as pie charts and bar charts. Plus, we’ll create a new variable to categorize age groups, giving you practical tools for effective data cleaning.
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Timestamps:
00:00 Intro to Data Cleaning
02:04 Reviewing the dataset
03:07 Upload dataset (CSV) to Jupyter notebook
04:07 Create a new Workbook and renaming the workbook (document)
04:45 Import libraries into your workbook to start coding
05:02 Python code to import the CSV file to Jupyter notebook & print out CSV dataset
06:26 Check information on the dataset
07:11 Review the variable names for misspellings, etc.
07:53 Drop a column by using python code
08:23 Create a new column naming it "Age Group" to group the ages in my dataset.
09:10 Checking for null values or N/A values
09:50 Dropping N/A (null) values
10:37 Checking for any duplicate values within the dataset
11:25 Dropping duplicates in the dataset using python code
11:54 Looking at the description of the dataset for "count, mean, std, min, max, etc."
12:27 Starting visualization
13:01 Pie chart visualization
16:19 Bar chart visualization
19:26 Pie chart visualization to compare another variable, "Season"
20:58 Bar chart visualization to review the variable "Age Group"
21:55 Bar chart visualization to review the variable "Age Group & Gender"
23:08 Thank you, and I hope you enjoyed the video. Please like and subscribe.
*** FREE code and dataset HERE***
The dataset used is "customer data on purchases" for a clothing store.
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Get the dataset here:
https://docs.google.com/spreadsheets/d/1oKXmVa8hqQeTIk2wsmD744nBhKlixY5Es6Wz0O5quz8/edit?usp=sharing
Get the code here: https://docs.google.com/document/d/1NbtEd2uQGTlSNZqsrONADdnIyhxGJfE2HE7mXulpOUM/edit?usp=sharing
**Get free resources to continue learning: **
https://www.excelcampus.com/161.php
===Great Books For Mastering Data Science and Data Cleaning===
Python For Data Analysis: https://amzn.to/4dQUOaF
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