英文:
Trying to show Count by department in Python
问题
以下是已翻译的部分：
这是一段简单的代码，目前我无法想到原因。我试图按部门按状态获取任务的数量。例如：
部门 任务 状态销售 销售 待处理销售 演示 完成技术 合并数据 完成技术 合并数据 待处理技术 演示 完成
我想要的是能够按部门分组统计状态列中已完成的数量。类似这样：
部门 状态 数量销售 已完成 1技术 已完成 2
到目前为止，我的代码可以看到所有部门的计数，但我无法找出最佳的分组方式。
参考代码：
counts = df['Department'].groupby('Status').count()
英文:
This is a simple piece of code for some reason I can't think of at the moment. I am trying to get the count of task by status by department. For instance something like this:
Department Task StatusSales Sell PendiingSales Presentation CompleteTech Merge Data CompleteTech Consolidate PendingTech Presentation Complete
What I want for here is to be able to break down by department of the count of completed in the status column. Something like this:
Department Status CountSales Completed 1Tech Completed 2
So far my code sees the count for all departments but I can't figure out the best way to group by.
Code for reference:
counts = df['Department'].groupby('Status').count()
答案1
得分: 3
你需要使用groupby方法对Department和Status进行分组；然后可以对每个分组使用count方法，并根据需要对Task列进行rename。然后，如果需要，可以使用reset_index方法将数据框重置为行索引：
df2 = df.groupby(['Department', 'Status']).count().rename(columns={'Task':'Count'}).reset_index()
输出结果（对于你的示例数据）：
Department Status Count0 Sales Complete 11 Sales Pendiing 12 Tech Complete 23 Tech Pending 1
然后，如果需要，可以根据Status进行筛选：
df2[df2['Status'] == 'Complete']
输出结果：
Department Status Count0 Sales Complete 12 Tech Complete 2
英文:
You need to groupby Department and Status; you can then count each group and rename the Task column if desired. Then you can use reset_index if required to return a row-indexed dataframe:
df2 = df.groupby(['Department', 'Status']).count().rename(columns={'Task':'Count'}).reset_index()
Output (for your sample data):
Department Status Count0 Sales Complete 11 Sales Pendiing 12 Tech Complete 23 Tech Pending 1
You can then filter that on Status if required:
df2[df2['Status'] == 'Complete']
Output:
Department Status Count0 Sales Complete 12 Tech Complete 2
答案2
得分: 1
这是一个可产生预期输出的替代方案，使用 pandas.GroupBy.count
df = df[df['状态'] == '完成'].groupby('部门')['任务'].count().reset_index()df.columns = ['部门', '计数']df['状态'] = '已完成'df = df.reindex(columns=['部门', '状态', '计数'])print(df)
英文:
Here is an alternative which will produce the expected output using pandas.GroupBy.count
df = df[df['Status'] == 'Complete'].groupby('Department')['Task'].count().reset_index()df.columns = ['Department', 'Count']df['Status'] = 'Completed'df = df.reindex(columns=['Department', 'Status', 'Count'])print(df)
Department Status Count0 Sales Completed 11 Tech Completed 2
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