Python Bar Charts

Question

I am trying to build time series histograms in Python. There was a similar question, but in R. So basically, I need the same thing, but I'm really bad at R. In my dataset there are usually 48 values ​​per day. Where - 9999 represents the missing data. The following is sample data.

I started by reading in data and building a pandas DataFrame .

 import pandas as pd df = pd.read_csv('sample.csv', parse_dates=True, index_col=0, na_values='-9999') print df <class 'pandas.core.frame.DataFrame'> DatetimeIndex: 336 entries, 2008-07-25 14:00:00 to 2008-08-01 13:30:00 Data columns (total 1 columns): 159.487691046 330 non-null values dtypes: float64(1) 

Now I can group the data by day:

 daily = df.groupby(lambda x: x.date()) 

But then I got stuck. I do not know how to use this with matplotlib to get my histogram timers. Any help is appreciated, not necessarily using pandas .

Answer 1

Make a histogram and use matplotlib pcolor .

We need to evenly group the groups, so we make the beans manually based on the range of your sample data.

 In [26]: bins = np.linspace(0, 360, 10) 

Apply a histogram to each group.

 In [27]: f = lambda x: Series(np.histogram(x, bins=bins)[0], index=bins[:-1]) In [28]: df1 = daily.apply(f) In [29]: df1 Out[29]: 0 40 80 120 160 200 240 280 320 2008-07-25 0 0 0 3 18 0 0 0 0 2008-07-26 2 0 0 0 17 6 13 1 8 2008-07-27 4 3 10 0 0 0 0 0 31 2008-07-28 0 7 15 0 0 0 0 6 20 2008-07-29 0 0 0 0 0 0 20 26 0 2008-07-30 10 1 0 0 0 0 1 25 9 2008-07-31 30 4 1 0 0 0 0 0 12 2008-08-01 0 0 0 0 0 0 0 14 14 

Following your related example in R, the horizontal axis should be the date, and the vertical axis should be the range of bins. The histogram values ​​are a heat map.

 In [30]: pcolor(df1.T) Out[30]: <matplotlib.collections.PolyCollection at 0xbb60e2c> 

It remains to mark the axis. This answer should help.