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.