Pandas: Finding average values of dataframe by hour & month

Question

Assume I have a df:

timestamp             value1     value2
01-01-2010 00:00:00       10          5
30-01-2019 00:00:00        5          1
01-02-2015 12:00:00        1          0
25-02-2007 05:00:00       10         10
01-02-2015 05:00:00       10          1

I would like to plot a time series graph based on mean value of columns 'value1' & 'value2' based only on hour & month of the dataset. Desired df & graph may look something like this:

hour-month     value1   value2
00-01             7.5        3
05-02              10      5.5
12-02               1        0

I'm new to Python; please advise

Answer 1

First convert column to datetimes by to_datetime , then aggregate mean with Series.dt.strftime for convert datetimes to HH-mm strings and last plot by DataFrame.plot :

df['timestamp'] = pd.to_datetime(df['timestamp'], dayfirst=True)

df1 = df.groupby(df['timestamp'].dt.strftime('%H-%m')).mean()

print (df1)
           value1  value2
timestamp                
00-01         7.5     3.0
05-02        10.0     5.5
12-02         1.0     0.0

df1.plot()

EDIT:

df['timestamp'] = pd.to_datetime(df['timestamp'], dayfirst=True)

df1 = df.groupby(df['timestamp'].map(lambda x: x.replace(year=2020, day=1))).mean()

print (df1)
                     value1  value2
timestamp                          
2020-01-01 00:00:00     7.5     3.0
2020-02-01 05:00:00    10.0     5.5
2020-02-01 12:00:00     1.0     0.0

df2 = df1.rename_axis('col', axis=1).stack().reset_index(name='vals')
print (df2)
            timestamp     col  vals
0 2020-01-01 00:00:00  value1   7.5
1 2020-01-01 00:00:00  value2   3.0
2 2020-02-01 05:00:00  value1  10.0
3 2020-02-01 05:00:00  value2   5.5
4 2020-02-01 12:00:00  value1   1.0
5 2020-02-01 12:00:00  value2   0.0

---

import plotly.express as px

#https://plotly.com/python/line-charts/
fig = px.line(df2, x="timestamp", y="vals", color='col')
#https://plotly.com/python/time-series/
fig.update_xaxes(
    dtick="timestamp",
    tickformat="%H\n%m")
fig.show()