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DataCamp - Cleaning Data in Python | Joanna

joannaoyzl.github.io · 3,492 words · saved by 1 readers

Datacamp course notes on data cleaning.

Datacamp course notes on data cleaning. Common Data Problems Inconsistent column names (capitalization) Missing data Outliers Duplicate rows (can bias analysis and should be dropped) Untidy Need to process between colums Column types can signal unexpected data values 1 2 3 4 5 6 import pandas as pd df.head() df.tail() df.columns #returns column names df.shape #returns dimension df.info() #additional info about the df Exploratory Data Analysis Frequency count value_counts() is a method we used here to count the number of unique values in each column in descending order 1 2 3 4 5 6 df.info() #kn

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