NONE_VIN = (df["VIN"].isnull()) | (df["VIN"].apply(lambda x: str(x).isspace()))
df_null = df[NONE_VIN]
df_not_null = df[~NONE_VIN]

df["VIN"]=df["VIN"].apply(lambda x: np.NaN if str(x).isspace() else x)
df_null = df[df["VIN"].isnull()]
df_not_null = df[df["VIN"].notnull()]

import pandas as pd
df1 = pd.DataFrame([{'col1':'a', 'col2':1}, {'col1':'b', 'col2':2}])
df2 = pd.DataFrame([{'col1':'a', 'col3':11}, {'col1':'c', 'col3':33}])

data = pd.merge(left=df1, right=df2, how='left', left_on='col1', right_on='col1')
print data
# 将NaN替换为None
print data.where(data.notnull(), None)

 col1 col2 col3
0 a  1 11
1 b  2 NaN
 col1 col2 col3
0 a  1 11
1 b  2 None