如何用Pandas Python统计Category列的总单元格数量

我想用Pandas统计DataFrame中Category列的所有单元格总数，尝试用df['Category'].value_counts()得到了各分类的出现次数（如下），但我需要的是把这些次数求和的总数量，该怎么操作？

已尝试的输出： #

Engineering & Information Technology        1159
Manufacturing                               1044
Vehicle Service                              915
Supply Chain                                 378
Energy - Solar & Storage                     374
Construction & Facilities                    296
Sales & Customer Support                     269
Finance                                      119
Charging                                     115
Environmental, Health & Safety                93
Autopilot & Robotics                          78
Operations & Business Support                 75
HR                                            64
Design                                        59
Vehicle Software                              40
Legal & Government Affairs                    18
External Relations & Employee Experience       2
Name: Category, dtype: int64

原始数据示例： #

Title   Category    Location
0   Technical Product Analyst   Engineering & Information Technology    Draper, Utah
1   Software Engineer   Engineering & Information Technology    Austin, Texas
2   Software Development Engineer   Engineering & Information Technology    Fremont, California
3   Global Supply Analyst   Supply Chain    Palo Alto, California
4   Software Support Engineer, Battery Automation ...   Engineering & Information Technology    Austin, Texas

解决方法 #

• 直接统计列的非空行数
  无需先执行value_counts，直接调用count()方法就能得到Category列的非空单元格总数，这是最直接高效的方式：

  df['Category'].count()
  

• 对value_counts结果求和
  如果你已经生成了value_counts的结果，可以直接对其求和得到总数：

  df['Category'].value_counts().sum()
  

• 通过DataFrame总行数获取
  若确认Category列没有缺失值，也可以直接取DataFrame的总行数：

  df.shape[0]
  

内容的提问来源于stack exchange，提问作者Michelle