CODEWITHSUNDEEP
python
Shane Markus
Shane Markus

Reputation: 9

How to plot daily plots from yearly time series

I have hourly ozone data over a multi year period in a pandas dataframe. I need to create plots of the ozone data for every day of the year (i.e. 365 plots for the year). The time series is in the following format:

    time_lt
3   1980-04-24 17:00:00
4   1980-04-24 18:00:00
5   1980-04-24 19:00:00
6   1980-04-24 20:00:00
7   1980-04-24 21:00:00
8   1980-04-24 22:00:00
9   1980-04-24 23:00:00
10  1980-04-25 00:00:00
11  1980-04-25 01:00:00
12  1980-04-25 02:00:00
13  1980-04-25 03:00:00
14  1980-04-25 04:00:00

How would I group the data by every day in order to plot each? what is the most efficient way of coding this?

Thanks!

Upvotes: 0

Views: 412

Answers (2)

crayxt
crayxt

Reputation: 2405

You can group on the fly:

import pandas as pd
from io import StringIO

df = pd.read_csv(StringIO(
"""id   time_lt
3   1980-04-24 17:00:00
4   1980-04-24 18:00:00
5   1980-04-24 19:00:00
6   1980-04-24 20:00:00
7   1980-04-24 21:00:00
8   1980-04-24 22:00:00
9   1980-04-24 23:00:00
10  1980-04-25 00:00:00
11  1980-04-25 01:00:00
12  1980-04-25 02:00:00
13  1980-04-25 03:00:00
14  1980-04-25 04:00:00"""), sep=" \s+")

df['time_lt'] = pd.to_datetime(df['time_lt'])
>>> df.groupby(df.time_lt.dt.floor('1D')).count()
            id  time_lt
time_lt
1980-04-24   7        7
1980-04-25   5        5

In theory, you can write a plotting function and apply it directly to the groupby result. But then it will be harder to control it. Since plotting itself will still be slowest operation in this chain, you can safely do simple iteration over dates.

Upvotes: 0

Epsi95
Epsi95

Reputation: 9047

Find comments inline

df['time_lt'] = pd.to_datetime(df['time_lt'])

# you can extract day, month, year
df['day'] = df['time_lt'].dt.day
df['month'] = df['time_lt'].dt.month
df['year'] = df['time_lt'].dt.year

#then use groupby
grouped = df.groupby(['day', 'month', 'year'])

# now you can plot individual groups

Upvotes: 1

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