如何使用熊猫删除在数据框中具有空列的行

我必须删除该列的整个行，该行没有任何价值，我的数据框看起来像

Name   place    phonenum

mike   china     12344
       ireland    897654
suzzi  japan      09876
chang  china      897654
       Australia  897654
       india      876543

所需的输出应为

Name   place    phonenum

mike   china     12344
suzzi  japan      09876
chang  china      897654

我用过df1=df[df.Name == ''] 我得到的输出

  Name   place    phonenum

请帮我

If Name is column:

print (df.columns)
Index(['Name', 'place', 'phonenum'], dtype='object')

Need change == to != for not equal if missing values are empty strings:

print (df)
    Name      place  phonenum
0   mike      china     12344
1           ireland    897654
2  suzzi      japan      9876
3  chang      china    897654
4         Australia    897654
5             india    876543

df1 = df[df.Name != '']
print (df1)
    Name  place  phonenum
0   mike  china     12344
2  suzzi  japan      9876
3  chang  china    897654

If in first columns are NaNs use dropna with specify column for check:

print (df)
    Name      place  phonenum
0   mike      china     12344
1    NaN    ireland    897654
2  suzzi      japan      9876
3  chang      china    897654
4    NaN  Australia    897654
5    NaN      india    876543

df1 = df.dropna(subset=['Name'])
print (df1)
    Name  place  phonenum
0   mike  china     12344
2  suzzi  japan      9876
3  chang  china    897654