从 pandas DataFrame 中提取单个类别的计数
Extract count of single category from a pandas DataFrame
我目前有一个 DataFrame,其中包含有关从一个职位发送到另一个职位的电子邮件的信息。
fromJobtitle toJobtitle e-mails
0 CEO CEO 65
1 CEO Director 23
2 CEO Employee 56
3 CEO In House Lawyer 7
4 CEO Manager 104
.. ... ... ...
87 Vice President Managing Director 112
88 Vice President President 385
89 Vice President Trader 78
90 Vice President Unknown 1088
91 Vice President Vice President 2304
我正在寻找一种方法,以便可以获取每个职位的总数。
示例输出为:
totalJobtitle e-mails
0 CEO 670
1 Managing Director 2341
2 Vice President 4720
3 Employee 3560
4 Trader 250
我可以使用的一个小例子
d = {'fromJobtitle': ["CEO", "CEO","VicePresident","VicePresident"], 'mail': [3, 4, 5, 6 ]}
df = pd.DataFrame(data=d)
df:
fromJobtitle mail
0 CEO 3
1 CEO 4
2 VicePresident 5
3 VicePresident 6
现在这个:
df = pd.pivot_table(df, index=['fromJobtitle'],values=['mail'],aggfunc=np.sum)
df:
fromJobtitle mail
CEO 7
VicePresident 11
函数来源:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.pivot_table.html
我目前有一个 DataFrame,其中包含有关从一个职位发送到另一个职位的电子邮件的信息。
fromJobtitle toJobtitle e-mails
0 CEO CEO 65
1 CEO Director 23
2 CEO Employee 56
3 CEO In House Lawyer 7
4 CEO Manager 104
.. ... ... ...
87 Vice President Managing Director 112
88 Vice President President 385
89 Vice President Trader 78
90 Vice President Unknown 1088
91 Vice President Vice President 2304
我正在寻找一种方法,以便可以获取每个职位的总数。 示例输出为:
totalJobtitle e-mails
0 CEO 670
1 Managing Director 2341
2 Vice President 4720
3 Employee 3560
4 Trader 250
我可以使用的一个小例子
d = {'fromJobtitle': ["CEO", "CEO","VicePresident","VicePresident"], 'mail': [3, 4, 5, 6 ]}
df = pd.DataFrame(data=d)
df:
fromJobtitle mail
0 CEO 3
1 CEO 4
2 VicePresident 5
3 VicePresident 6
现在这个:
df = pd.pivot_table(df, index=['fromJobtitle'],values=['mail'],aggfunc=np.sum)
df:
fromJobtitle mail
CEO 7
VicePresident 11
函数来源: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.pivot_table.html