I took an excel sheet which has dates and some values and want to convert them to pandas dataframe and select only rows which are between certain dates.
For some reason I cannot select a row by date index
Raw Data in Excel file
MCU
Timestamp 50D 10P1 10P2 10P3 10P6 10P9 10P12
12-Feb-15 25.17 5.88 5.92 5.98 6.18 6.23 6.33
11-Feb-15 25.9 6.05 6.09 6.15 6.28 6.31 6.39
10-Feb-15 26.38 5.94 6.05 6.15 6.33 6.39 6.46
Code
xls = pd.ExcelFile('e:/Data.xlsx')
vols = xls.parse(asset.upper()+'VOL',header=1)
vols.set_index('Timestamp',inplace=True)
Data before set_index
Timestamp 50D 10P1 10P2 10P3 10P6 10P9 10P12 25P1 25P2 \
0 2015-02-12 25.17 5.88 5.92 5.98 6.18 6.23 6.33 2.98 3.08
1 2015-02-11 25.90 6.05 6.09 6.15 6.28 6.31 6.39 3.12 3.17
2 2015-02-10 26.38 5.94 6.05 6.15 6.33 6.39 6.46 3.01 3.16
Data after set_index
50D 10P1 10P2 10P3 10P6 10P9 10P12 25P1 25P2 25P3 \
Timestamp
2015-02-12 25.17 5.88 5.92 5.98 6.18 6.23 6.33 2.98 3.08 3.21
2015-02-11 25.90 6.05 6.09 6.15 6.28 6.31 6.39 3.12 3.17 3.32
2015-02-10 26.38 5.94 6.05 6.15 6.33 6.39 6.46 3.01 3.16 3.31
Output
>>> vols.index
<class 'pandas.tseries.index.DatetimeIndex'>
[2015-02-12, ..., NaT]
Length: 1478, Freq: None, Timezone: None
>>> vols[date(2015,2,12)]
*** KeyError: datetime.date(2015, 2, 12)
I would expect this not to fail, and also I should be able to select a range of dates. Tried so many combinations but not getting it.
Using a datetime.date instance to try to retrieve the index won't work, you just need a string representation of the date, e.g. '2015-02-12' or '2015/02/14'.
Secondly, vols[date(2015,2,12)] is actually looking in your DataFrame's column headings, not the index. You can use loc to fetch row index labels instead. For example you could write vols.loc['2015-02-12']
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