Drop Row se todos os valores forem nan
df = df.dropna(axis = 0, how = 'all')
Tender Turtle
df = df.dropna(axis = 0, how = 'all')df = df[df['EPS'].notna()]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)
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')#return a subset of the dataframe where the column name value != NaN
df.loc[df['column name'].isnull() == False] In [30]: df.dropna(subset=[1]) #Drop only if NaN in specific column (as asked in the question)
Out[30]:
0 1 2
1 2.677677 -1.466923 -0.750366
2 NaN 0.798002 -0.906038
3 0.672201 0.964789 NaN
5 -1.250970 0.030561 -2.678622
6 NaN 1.036043 NaN
7 0.049896 -0.308003 0.823295
9 -0.310130 0.078891 NaN