Cleaning a messy and dirty set of data with python
gray thomson
Product Data Analyst
Data Analyst
Python
In [25]:
"C:/Users/SterSc/Downloads/food_coded.csv"
"display.max_columns"
"Letter_grading"
map_to_letter_grade
"Letter_grading"
#Based on the dataset source info, replacing every confusing 1, 2 data
"comfort_food_reasons_coded.1"
#Changing the scores from (1 is the hieghest) to (10 is the heighest)
"eating_changes_collage_entrance_simple"
#Removing unnecessary columns
#reordering columns
'Letter_grading'
In [38]:
"food chain data"
In [ ]:
In [ ]:
