Replace column values | Covert string to numeric | loc and replace function in python

Published: 14 February 2021
on channel: Data Science Desk

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I used a real dataset to demonstrate how to replace column values/records and convert the variable type from string/object to numeric/float/integer. I used .loc and .replace functions in python Jupyter notebook.
Sometimes, pandas reads a typical numeric variable such as "age" as string if this variable has non-numeric values in the records. In this situation, we must replace the non-numeric values into empty cell (to consider as missing values). Then, we have to convert the variable type from string to numeric.

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