Pandas X_axis hourly

Question

I have this little Pandascode:

graph = auswahl[['Volumenstrom_Außen', 'Vpunkt_Gesamt','Zuluft_Druck_10','Abluft_Druck_10']]
a = graph.plot(figsize=[50,10])
a.set(ylabel="m³/h", xlabel="Zeit", title="Volumenströme")#,ylim=[0,100])
a.legend(loc="upper left")
plt.show()

How can I set the X-Axis showing every Hour?

the dataframe looks like this:

    Volumenstrom_Außen  Vpunkt_Gesamt   Zuluft_Druck    Abluft_Druck
Zeit                
2018-02-15 16:49:00     1021.708443     752.699     49.328  46.811
2018-02-15 16:49:15     1021.708443     752.699     49.328  46.811
2018-02-15 16:49:30     1021.708443     752.699     49.328  46.811
2018-02-15 16:49:45     1021.708443     752.699     49.328  46.811
2018-02-15 16:50:00     1021.708443     752.699     49.328  46.811
2018-02-15 16:50:15     1021.708443     752.699     49.328  46.811
2018-02-15 16:50:30     1021.708443     752.699     49.328  46.811
2018-02-15 16:50:45     1021.708443     752.699     49.328  46.811
2018-02-15 16:51:00     1092.171094     752.699     49.328  46.811
2018-02-15 16:51:15     1092.171094     752.699     49.328  46.811

missing some code? how are you calling plot on a list of list. What is auswahl — vumaasha, Feb 23 '18 at 12:15

score 1 · Accepted Answer · answered Feb 23 '18 at 13:39

1

Let's take this example dataframe, whose index is at minute granularity

import pandas as pd
import random
ts_index = pd.date_range('1/1/2000', periods=1000, freq='T')
v1 = [random.random() for i in range(1000)]
v2 = [random.random() for i in range(1000)]
v3 = [random.random() for i in range(1000)]
ts_df = pd.DataFrame({'v1':v1,'v2':v2,'v3':v3},index=ts_index)
ts_df.head()



                         v1           v2        v3
2000-01-01 00:00:00     0.593039    0.017351    0.742111
2000-01-01 00:01:00     0.563233    0.837362    0.869767
2000-01-01 00:02:00     0.453925    0.962600    0.690868
2000-01-01 00:03:00     0.757895    0.123610    0.622777
2000-01-01 00:04:00     0.759841    0.906674    0.263902

We could use pandas.DataFrame.resample to downsample this data to hourly granularity, like shown below

hourly_mean_df = ts_df.resample('H').mean() # you can use .sum() also
hourly_mean_df.head()

                          v1          v2         v3
2000-01-01 00:00:00     0.516001    0.461119    0.467895
2000-01-01 01:00:00     0.530603    0.458208    0.550892
2000-01-01 02:00:00     0.472090    0.522278    0.508345
2000-01-01 03:00:00     0.515713    0.486906    0.541538
2000-01-01 04:00:00     0.514543    0.478097    0.489217

Now you can plot this hourly summary

hourly_mean_df.plot()

answered Feb 23 '18 at 13:39

vumaasha

2,765
4
27
41

I do not want to resample the Data. Just show every hour unter the x-axis. The df is over one week long and plot() showes just the day, not the hours. – kolja Feb 23 '18 at 13:43
you should make it clear, what you want in the question then – vumaasha Feb 23 '18 at 13:44
do you just want to set the tick at every hour? – vumaasha Feb 23 '18 at 13:44
Yes, tick at every hour :-) – kolja Feb 23 '18 at 13:46
looks like a duplicate of this question. https://stackoverflow.com/questions/12945971/pandas-timeseries-plot-setting-x-axis-major-and-minor-ticks-and-labels – vumaasha Feb 23 '18 at 13:48
no, the question bihind yopur link is not from me, and does not help me – kolja Feb 23 '18 at 13:52
@kolja it does show how to use custom time units for ticks. take a look properly – vumaasha Feb 23 '18 at 13:56

Pandas X_axis hourly

1 Answers1