问题描述
目标
我有一个 Pandas 数据框,如下所示,它有多个列,并且想要获取列的总数,MyColumn
.
I have a Pandas data frame, as shown below, with multiple columns and would like to get the total of column, MyColumn
.
数据框 - df
:
打印 df
X MyColumn Y Z
0 A 84 13.0 69.0
1 B 76 77.0 127.0
2 C 28 69.0 16.0
3 D 28 28.0 31.0
4 E 19 20.0 85.0
5 F 84 193.0 70.0
<小时>
我的尝试:
我尝试使用 groupby
和 .sum()
获取列的总和:
I have attempted to get the sum of the column using groupby
and .sum()
:
Total = df.groupby['MyColumn'].sum()
print Total
这会导致以下错误:
TypeError: 'instancemethod' object has no attribute '__getitem__'
<小时>
预期输出
我希望输出如下:
319
或者,我希望 df
使用标题为 TOTAL
的新 row
进行编辑,其中包含总数:
Or alternatively, I would like df
to be edited with a new row
entitled TOTAL
containing the total:
X MyColumn Y Z
0 A 84 13.0 69.0
1 B 76 77.0 127.0
2 C 28 69.0 16.0
3 D 28 28.0 31.0
4 E 19 20.0 85.0
5 F 84 193.0 70.0
TOTAL 319
推荐答案
你应该使用 sum
:
You should use sum
:
Total = df['MyColumn'].sum()
print (Total)
319
然后你使用 loc
与 Series
,在这种情况下,索引应设置为与您需要求和的特定列相同:
Then you use loc
with Series
, in that case the index should be set as the same as the specific column you need to sum:
df.loc['Total'] = pd.Series(df['MyColumn'].sum(), index = ['MyColumn'])
print (df)
X MyColumn Y Z
0 A 84.0 13.0 69.0
1 B 76.0 77.0 127.0
2 C 28.0 69.0 16.0
3 D 28.0 28.0 31.0
4 E 19.0 20.0 85.0
5 F 84.0 193.0 70.0
Total NaN 319.0 NaN NaN
因为如果你传递标量,所有行的值都会被填充:
because if you pass scalar, the values of all rows will be filled:
df.loc['Total'] = df['MyColumn'].sum()
print (df)
X MyColumn Y Z
0 A 84 13.0 69.0
1 B 76 77.0 127.0
2 C 28 69.0 16.0
3 D 28 28.0 31.0
4 E 19 20.0 85.0
5 F 84 193.0 70.0
Total 319 319 319.0 319.0
另外两个解决方案是 at
和 ix
查看以下应用:
Two other solutions are with at
, and ix
see the applications below:
df.at['Total', 'MyColumn'] = df['MyColumn'].sum()
print (df)
X MyColumn Y Z
0 A 84.0 13.0 69.0
1 B 76.0 77.0 127.0
2 C 28.0 69.0 16.0
3 D 28.0 28.0 31.0
4 E 19.0 20.0 85.0
5 F 84.0 193.0 70.0
Total NaN 319.0 NaN NaN
<小时>
df.ix['Total', 'MyColumn'] = df['MyColumn'].sum()
print (df)
X MyColumn Y Z
0 A 84.0 13.0 69.0
1 B 76.0 77.0 127.0
2 C 28.0 69.0 16.0
3 D 28.0 28.0 31.0
4 E 19.0 20.0 85.0
5 F 84.0 193.0 70.0
Total NaN 319.0 NaN NaN
注意:自 Pandas v0.20 起,ix
已被弃用.请改用 loc
或 iloc
.
Note: Since Pandas v0.20, ix
has been deprecated. Use loc
or iloc
instead.
这篇关于获取 Pandas 列的总数的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持跟版网!