Python Pandas: plot values against hour and date

Question

I have a Panda Dataframe prices with the following structure:

prices
Out[28]: 
                      FCR-N   FCR-D
Period                             
2016-01-01 00:00:00  28.949   5.285
2016-01-01 01:00:00  28.820   5.314
2016-01-01 02:00:00  28.734   5.330
2016-01-01 03:00:00  28.822   5.292
2016-01-01 04:00:00  28.822   5.251
                    ...     ...
2020-04-30 19:00:00   8.767  11.587
2020-04-30 20:00:00   8.441   6.528
2020-04-30 21:00:00   7.857   8.275
2020-04-30 22:00:00   7.873   7.896
2020-04-30 23:00:00   7.893   8.046

[37967 rows x 2 columns]

I would like to get a plot similar to the one below with hours on y-axis from the Period column, dates on the x-axis from the Period column, and the corresponding color on the graph set by the value in the FCR-N column.

I haven't figured out how to obtain such a plot. What would be the best way to do it?

Looks like a heatmap? You can use seaborn for that seaborn.pydata.org/generated/seaborn.heatmap.html . — k88
– k88, Commented May 11, 2020 at 7:20

jezrael · Accepted Answer · 2020-05-11 07:26:19Z

1

Use DataFrame.pivot_table with some aggregation funecion, e.g. sum and then seaborn.heatmap:

import seaborn as sns

df1 = df.pivot_table(index=df.index.hour, 
                     columns=df.index.year,
                     values='FCR-N',
                     fill_value=0,
                     aggfunc='sum')
print (df1)
Period    2016   2020
Period               
0       28.949  0.000
1       28.820  0.000
2       28.734  0.000
3       28.822  0.000
4       28.822  0.000
19       0.000  8.767
20       0.000  8.441
21       0.000  7.857
22       0.000  7.873
23       0.000  7.893

sns.heatmap(df1)

answered May 11, 2020 at 7:26

jezrael

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