pandas 如何使用pandas删除数据框中具有空列的行
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how to remove a row which has empty column in a dataframe using pandas
提问by tiru
I have to remove entire row with the column, which has no value my dataframe looks like
我必须用列删除整行，我的数据框看起来没有价值
Name place phonenum
mike china 12344
ireland 897654
suzzi japan 09876
chang china 897654
Australia 897654
india 876543
required output should be
所需的输出应该是
Name place phonenum
mike china 12344
suzzi japan 09876
chang china 897654
I have used df1=df[df.Name == '']I got output
我用过df1=df[df.Name == '']我有输出
Name place phonenum
Please help me
请帮我
回答by jezrael
If Nameis column:
如果Name是列：
print (df.columns)
Index(['Name', 'place', 'phonenum'], dtype='object')
Need change ==to !=for not equal if missing values are empty strings:
需要改变==以!=不等于如果缺失值是空字符串：
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 dropnawith specify column for check:
如果在第一列中NaN使用dropna指定列进行检查：
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
回答by u9862891
DataFrame dropna() method will drop entire row if any value in the row is missing.
如果行中的任何值丢失，DataFrame dropna() 方法将删除整行。
df1 = df.dropna()
回答by StudentAtLU
In my case, I had a bunch of fields with dates, strings, and one column for values (also called "Value"). I tried all suggestions above, but what actually worked was to drop NA records for the "Value" field.
就我而言，我有一堆带有日期、字符串和一列值（也称为“值”）的字段。我尝试了上面的所有建议，但真正有效的是删除“值”字段的 NA 记录。
df = df.dropna(subset=['Value'])
df = df.dropna(subset=['Value'])
