Python 向透视表添加行和列合计失败
我想显示行和列合计。我使用margin=True，但输出不显示行总数，如下代码和输出所示：Python 向透视表添加行和列合计失败,python,pandas,rowsum,column-sum,Python,Pandas,Rowsum,Column Sum,我想显示行和列合计。我使用margin=True，但输出不显示行总数，如下代码和输出所示： import pandas as pd df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1") df2['received'] = pd.to_datetime(df2['received']) df2['sent'] = pd.to_datetime(df2
import pandas as pd
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])\
.pivot_table(index=['site'], values=['received','sent'],\
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
pvt_all=pvt_all[['received','sent','to_send']]
pvt_all
received sent to_send
site
2 32.0 27.0 5.0
3 20.0 17.0 3.0
4 33.0 31.0 2.0
5 40.0 31.0 9.0
All 125.0 106.0 19.0
date site received sent
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received sent Total
site
2 32 27 59
3 20 17 37
4 33 31 64
5 40 31 71
All 125 106 231
你能发布样本数据吗？您可能想看看@MattR，这里的代码中已经有示例数据：df2=pd.read\u csv（“）@马特，我已经读过你分享的podt，认为它不适用于我的案例。感谢你为什么要添加示例数据而不是dropbox是双重原因。有些人不想去外部网站帮助回答你的问题。而且，如果将来链接断开，那些来这篇文章的人将无法跟进。我建议你添加示例数据并阅读如何创建好的熊猫示例。你越容易为那些帮助你的人提供帮助，你就会得到越多的帮助：）@MattR，谢谢你的解释和澄清。现在，我明白了原因。请再次检查，我已更新了我的问题。谢谢，但对我来说不起作用。8 pvt_all=df2.dropna（axis=0，how='all'，subset=['received'，'sent']）。pivot_表（index='site'，value=['received'，'sent']，aggfunc='count'，margins=True，dropna=False）。eval（'Total=received+sent'）--->9 pvt_all['to_send']=pvt_all['sent']10 pvt_all=pvt_all['received'，'send'，'to_']11 pvt_所有类型错误：“非类型”对象不可下标
received sent Total
site
2 32 27 59
3 20 17 37
4 33 31 64
5 40 31 71
All 125 106 231
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
import pandas as pd
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])\
.pivot_table(index=['site'], values=['received','sent'],\
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
#pvt_all['Total'] = pvt_all.received + pvt_all.sent + pvt_all.to_send
pvt_all['Total'] = pvt_all.sum(axis=1) #Add Total column for row subtotal \
#and Total
pvt_all=pvt_all[['received','sent','to_send','Total']]
pvt_all
received sent to_send Total
site
2 32.0 27.0 5.0 64.0
3 20.0 17.0 3.0 40.0
4 33.0 31.0 2.0 66.0
5 40.0 31.0 9.0 80.0
All 125.0 106.0 19.0 250.0