How to Clean Data With Pandas
How to Deal With Missing Values, Outliers, and Dates using Python
Published in
8 min readNov 28, 2022
Once you collect the data, the most time-consuming task of every Data (Science) project starts: cleaning the data.
Data always come messy: from wrong data from human mistakes (either voluntary or involuntary) to missing values (either filled by empty or null), and sometimes you have to manage with malformed date fields you can’t interpret the right way…
