pandas dataframe remove NaN code example

Example 1: remove nan from list python

cleanedList = [x for x in countries if str(x) != 'nan']

Example 2: drop if nan in column pandas

df = df[df['EPS'].notna()]

Example 3: how to delete nan values in python

x = x[~numpy.isnan(x)]

Example 4: remove rows or columns with NaN value

df.dropna()     #drop all rows that have any NaN values
df.dropna(how='all')

Example 5: dropping nan in pandas dataframe

df.dropna(subset=['name', 'born'])

Example 6: 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)