After using the asfreq method to change the frequency of a time-series DataFrame from None to something e.g. 15Min the cursor position in matplotlib graphs of that DataFrame is no longer correct (usually shows a datetime just after the unix epoch). The following demonstrates this (NB dt in df1 is not a constant):

df1 = pandas.read_csv('tseries1.csv', names=['tstamp', 'Q'], parse_dates=True, index_col='tstamp').clip_lower(0).fillna(0) df1['T'] = pandas.read_csv('tseries2.csv', names=['tstamp', 'T'], parse_dates=True, index_col='tstamp', squeeze=True).clip_lower(0).fillna(0) df2 = df1.asfreq(freq='15Min', method='ffill') # NB df1.index.freq is None # NB df2.index.freq is <15 * Minutes> df1.plot() df2.plot() plt.show() 

I find the Matplotlib cursor position to be invaluable when looking for features in very long time-series.

Versions:

• pandas master (commit ID 764b444)
• numpy 1.8
• matplotlib 1.3.0