[英]How to read the data in Pandas's dataframe row wise and plot the values as a timeseries if column represents months and index is years?
[英]Pandas: Read a CSV of timeseries data with 'column' header as row element
是否可以以這種格式讀取CSV文件:
2013-01-01,A,1
2013-01-02,A,2
2013-01-03,A,3
2013-01-04,A,4
2013-01-05,A,5
2013-01-01,B,1
2013-01-02,B,2
2013-01-03,B,3
2013-01-04,B,4
2013-01-05,B,5
進入一個像這樣結束的DataFrame:
A B
2013-01-01 1 1
2013-01-02 2 2
2013-01-03 3 3
2013-01-04 4 4
2013-01-05 5 5
我在I / O文檔中看不到任何內容( http://pandas.pydata.org/pandas-docs/dev/io.html )
在讀取DataFrame 后,為什么不重塑(pivot)?
In [1]: df = pd.read_csv('foo.csv', sep=',', parse_dates=[0], header=None,
names=['Date', 'letter', 'value'])
In [2]: df
Out[2]:
Date letter value
0 2013-01-01 00:00:00 A 1
1 2013-01-02 00:00:00 A 2
2 2013-01-03 00:00:00 A 3
3 2013-01-04 00:00:00 A 4
4 2013-01-05 00:00:00 A 5
5 2013-01-01 00:00:00 B 1
6 2013-01-02 00:00:00 B 2
7 2013-01-03 00:00:00 B 3
8 2013-01-04 00:00:00 B 4
9 2013-01-05 00:00:00 B 5
In [3]: df.pivot(index='Date', columns='letter', values='value')
Out[3]:
letter A B
Date
2013-01-01 1 1
2013-01-02 2 2
2013-01-03 3 3
2013-01-04 4 4
2013-01-05 5 5
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