Pandas Resampling error: Only valid with DatetimeIndex or PeriodIndex

PythonPandas

Python Problem Overview


When using panda's resample function on a DataFrame in order to convert tick data to OHLCV, a resampling error is encountered.

How should we solve the error?

data = pd.read_csv('tickdata.csv', header=None, names=['Timestamp','Price','Volume']).set_index('Timestamp')
data.head()

enter image description here

# Resample data into 30min bins
ticks = data.ix[:, ['Price', 'Volume']]
bars = ticks.Price.resample('30min', how='ohlc')
volumes = ticks.Volume.resample('30min', how='sum')

This gives the error:

TypeError: Only valid with DatetimeIndex or PeriodIndex

Python Solutions


Solution 1 - Python

Convert the integer timestamps in the index to a DatetimeIndex:

data.index = pd.to_datetime(data.index, unit='s')

This interprets the integers as seconds since the Epoch.


For example, given

data = pd.DataFrame(
    {'Timestamp':[1313331280, 1313334917, 1313334917, 1313340309, 1313340309], 
     'Price': [10.4]*3 + [10.5]*2, 'Volume': [0.779, 0.101, 0.316, 0.150, 1.8]})
data = data.set_index(['Timestamp'])
#             Price  Volume
# Timestamp                
# 1313331280   10.4   0.779
# 1313334917   10.4   0.101
# 1313334917   10.4   0.316
# 1313340309   10.5   0.150
# 1313340309   10.5   1.800

data.index = pd.to_datetime(data.index, unit='s')

yields

                     Price  Volume
2011-08-14 14:14:40   10.4   0.779
2011-08-14 15:15:17   10.4   0.101
2011-08-14 15:15:17   10.4   0.316
2011-08-14 16:45:09   10.5   0.150
2011-08-14 16:45:09   10.5   1.800

Then

ticks = data.ix[:, ['Price', 'Volume']]
bars = ticks.Price.resample('30min').ohlc()
volumes = ticks.Volume.resample('30min').sum()

can be computed:

In [368]: bars
Out[368]: 
                     open  high   low  close
2011-08-14 14:00:00  10.4  10.4  10.4   10.4
2011-08-14 14:30:00   NaN   NaN   NaN    NaN
2011-08-14 15:00:00  10.4  10.4  10.4   10.4
2011-08-14 15:30:00   NaN   NaN   NaN    NaN
2011-08-14 16:00:00   NaN   NaN   NaN    NaN
2011-08-14 16:30:00  10.5  10.5  10.5   10.5

In [369]: volumes
Out[369]: 
2011-08-14 14:00:00    0.779
2011-08-14 14:30:00      NaN
2011-08-14 15:00:00    0.417
2011-08-14 15:30:00      NaN
2011-08-14 16:00:00      NaN
2011-08-14 16:30:00    1.950
Freq: 30T, Name: Volume, dtype: float64

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Content TypeOriginal AuthorOriginal Content on Stackoverflow
QuestionNyxynyxView Question on Stackoverflow
Solution 1 - PythonunutbuView Answer on Stackoverflow