问题描述
我的 .csv 文件如下所示:
My .csv file looks like:
Area When Year Month Tickets
City Day 2015 1 14
City Night 2015 1 5
Rural Day 2015 1 18
Rural Night 2015 1 21
Suburbs Day 2015 1 15
Suburbs Night 2015 1 21
City Day 2015 2 13
包含 75 行.我想要一个行多索引和列多索引，看起来像:
containing 75 rows. I want both a row multiindex and column multiindex that looks like:
Area City Rural Suburbs
When Day Night Day Night Day Night
Year Month
2015 1 5.0 3.0 22.0 11.0 13.0 2.0
2 22.0 8.0 4.0 16.0 6.0 18.0
3 26.0 25.0 22.0 23.0 22.0 2.0
2016 1 20.0 25.0 39.0 14.0 3.0 10.0
2 4.0 14.0 16.0 26.0 1.0 24.0
3 22.0 17.0 7.0 24.0 12.0 20.0
我在 https 上阅读了 .read_csv 文档://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html
我可以通过以下方式获取行多索引:
I can get the row multiindex with:
df2 = pd.read_csv('c:\\Data\Tickets.csv', index_col=[2, 3])
我试过了:
df2 = pd.read_csv('c:\\Data\Tickets.csv', index_col=[2, 3], header=[1, 3, 5])
thinking [1, 3, 5] 获取城市"、农村"和郊区".如何获得上面显示的所需列多索引?
thinking [1, 3, 5] fetches 'City', 'Rural', and 'Suburbs'. How do I get the desired column multiindex shown above?
推荐答案
似乎您需要pivot_table 具有多个索引和多个列.
Seems like you need to pivot_table with multiple indexes and multiple columns.
从简单地读取您的 csv 开始
Start with just reading you csv plainly
df = pd.read_csv('Tickets.csv')
然后
df.pivot_table(index=['Year', 'Month'], columns=['Area', 'When'], values=['Tickets'])
使用您提供的输入数据，您将获得
With the input data you provided, you'd get
Area City Rural Suburbs
When Day Night Day Night Day Night
Year Month
2015 1 14.0 5.0 18.0 21.0 15.0 21.0
2 13.0 NaN NaN NaN NaN NaN
这篇关于需要带有 read_csv 的行和列的 MultiIndex的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！