if none in column remove row
import pandas as pd
df = df[pd.notnull(df['Gender'])]
if none in column remove row
import pandas as pd
df = df[pd.notnull(df['Gender'])]
drop null rows pandas
df.dropna()
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)
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