Data_Cleaning_Using_Python

Data Cleaning With Pandas and NumPy

1. Dropping Columns in a DataFrame
2. Changing the Index of a DataFrame
3. Tidying up Fields in the Data
4. Combining str Methods with NumPy to Clean Columns
5. Cleaning the Entire Dataset Using the applymap Function
6. Renaming Columns and Skipping Rows

Here are the datasets that I have used:

1. BL-Flickr-Images-Book.csv – A CSV file containing information about books from the British Library
2. university_towns.txt – A text file containing names of college towns in every US state
3. olympics.csv – A CSV file summarizing the participation of all countries in the Summer and Winter Olympics