Question

我想在pandas数据框中创建一列，以添加其他列的值（为0或1s）。该列称为“总和”

我的HEADPandas看起来像：

     Application  AnsSr sum  Col1 Col2 Col3 .... Col(n-2) Col(n-1) Col(n)
date 28-12-11      0.0   0.0  28/12/11      ....    ...Dates...    28/12/11
~00c        0      0.0   0.0  0    0     0  ....    0       0       0
~00pr       0      0.0   0.0  0    0     0  ....    0       0       0
~00te       0      0.0   0.0  0    0     1  ....    0       0       1

在pythoneverywhere中的图像中：

预期结果（假设不再有列

     Application  AnsSr sum  Col1  Col2  Col3 .... Col(n-2) Col(n-1) Col(n)
date 28-12-11      0.0   nan  28/12/11        ....    ...Dates...    28/12/11
~00c        0      0.0   0.0   0    0     0  ....    0      0        0
~00pr       0      0.0   0.0   0    0     0  ....    0      0        0
~00te       0      0.0   2     0    0     1  ....    0      0        1

如您所见，

即使某些列中的值为1s，“ sum”的值仍保持为0。我在做什么错了？

代码的基础是：

theMatrix=pd.DataFrame([datetime.today().strftime('%Y-%m-%d')],['Date'],['Application'])
theMatrix['Ans'] = 0
theMatrix['sum'] = 0

到目前为止一切都很好然后我用loc添加所有值。然后我想用

theMatrix.fillna(0, inplace=True)
# this being the key line:
theMatrix['sum'] = theMatrix.sum(axis=1)
theMatrix.sort_index(axis=0, ascending=True, inplace=True)

如您在结果中所见（附图），总和仍为0。我看了一下here或here以及熊猫documentation无济于事。实际上是表达式：

theMatrix['sum'] = theMatrix.sum(axis=1)

我从那里得到的。

通过以下方式更改最后一行：

theMatrix['sum'] = theMatrix[3:0].sum(axis=1)

为了避免对前三列求和，得出结果：

     Application  AnsSr sum  Col1  Col2  Col3 .... Col(n-2) Col(n-1) Col(n)
date 28-12-11      0.0   nan  28/12/11        ....    ...Dates...    28/12/11
~00c        0      0.0   nan   1    1     0  ....    0      0        0
~00pr       0      0.0   1.0   0    0     0  ....    0      0        1
~00te       0      0.0   0     0    0     0  ....    0      0        0

请注意两件事： a）'〜00c'行的总和是nan，但该行中有1。 b）在计算总和之前，代码theMatrix.fillna（0，inplace = True）应该将所有可能的nan都更改为0，所以总和永远都不应该是nan，因为理论上在任何列中都没有nan值[3： ]

那行不通。

有个主意吗？

谢谢

PS：更高版本，以防万一您想知道如何填充数据帧：读取和解析XML，行如下：

# myDocId being the name of the columns
# concept being the index.
theMatrix.loc[concept,myDocId]=1

Answer 1

如果我理解正确，那么可以为您提供帮助：

import pandas as pd
import datetime

#create dataframe following your example
theMatrix=pd.DataFrame([datetime.datetime.today().strftime('%Y-%m-%d')],['Date'],['Application'])
theMatrix['Ans'] = 0
theMatrix['col1'] = 1
theMatrix['col2'] = 1

# create 'sum' column with summed values from certain columns
theMatrix['sum'] = theMatrix['col1'] + theMatrix['col2']

Answer 2

您选择求和的任何数据，只需将其添加到列表中，然后使用该列表提供给sum函数（轴= 1）。这将为您提供所需的结果。这是与您的数据有关的示例。

样本文件数据：

Date,a,b,c
bad, bad, bad, bad # Used to simulate your data better
2018-11-19,1,0,0
2018-11-20,1,0,0
2018-11-21,1,0,1
2018-11-23,1,nan,0 # Nan here is just to represent the missing data
2018-11-28,1,0,1
2018-11-30,1,nan,1 # Nan here is just to represent the missing data
2018-12-02,1,0,1

代码：

import pandas as pd
df = pd.read_csv(yourdata.filename) # Your method of loading the data
#rows_to_sum = ['a','b','c'] # The rows you wish to summarize
rows_to_sum = df.columns[1:] # Alternate method to select remainder of rows.
df = df.fillna(0) # used to fill the NaN you were talking about below. 
df['sum'] = df[rows_to_sum][1:].astype(int).sum(axis=1) # skip the correct amount of rows here. 
# Also, the use of astype(int), is due to the bad data read from the top. So redefining it here, allows you to sum it appropriately. 
print(df)

输出：

       Date     a     b     c  sum
        bad   bad   bad   bad  NaN
 2018-11-19     1     0     0  1.0
 2018-11-20     1     0     0  1.0
 2018-11-21     1     0     1  2.0
 2018-11-23     1     0     0  1.0
 2018-11-28     1     0     1  2.0
 2018-11-30     1     0     1  2.0
 2018-12-02     1     0     1  2.0

python pandas求和列到求和列

2 个答案: