Answers for "pandas remove rows with nan values and reset index"

1

pandas drop row with nan

import pandas as pd

df = pd.DataFrame({'values_1': ['700','ABC','500','XYZ','1200'],
                   'values_2': ['DDD','150','350','400','5000'] 
                   })

df = df.apply (pd.to_numeric, errors='coerce')
df = df.dropna()
df = df.reset_index(drop=True)

print (df)
Posted by: Guest on February-16-2021
2

remove rows or columns with NaN value

df.dropna()     #drop all rows that have any NaN values
df.dropna(how='all')
Posted by: Guest on August-23-2020

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