Python pandas plot time-series with gap

Question

I am trying to plot a pandas DataFrame with TimeStamp indizes that has a time gap in its indizes. Using pandas.plot() results in linear interpolation between the last TimeSt

Answer 1

Try:

df.plot(x=df.index.astype(str))

You may want to customize ticks and tick labels.

EDIT

That works for me using pandas 0.17.1 and numpy 1.10.4.

All you really need is a way to convert the DatetimeIndex to another type which is not datetime-like. In order to get meaningful labels I chose str. If x=df.index.astype(str) does not work with your combination of pandas/numpy/whatever you can try other options:

df.index.to_series().dt.strftime('%Y-%m-%d')
df.index.to_series().apply(lambda x: x.strftime('%Y-%m-%d'))
...

I realized that resetting the index is not necessary so I removed that part.

Answer 2

In my case I had DateTimeIndex objects instead of TimeStamp, but the following works for me in pandas 0.24.2 to eliminate the time series gaps after converting the DatetimeIndex objects to string.

df = pd.read_sql_query(sql, sql_engine)
df.set_index('date'), inplace=True)
df.index = df.index.map(str)