Python pandas and matplotlib automatically filling in missing data

Question

Im very new to python and trying to figure out how to graph out some data which can have missing data for any given date.

The data is number of jobs completed (y), their rating (secondary Y), and date (x).

The graph looks how id like however jobs dont get completed each day so there are days where there is no data and the line on the graph just stops.

Is there a way to have it automatically connect the dots on the graph?

import matplotlib.pyplot as plt
import pandas as pd
import database


df = pd.DataFrame(database.getTasks("Pete"), columns=['date', 'rating', 'jobs']).set_index('date')

fig, ax = plt.subplots()
ax3 = ax.twinx()
rspine = ax3.spines['right']
rspine.set_position(('axes', 1.15))
ax3.set_frame_on(True)
ax3.patch.set_visible(False)

df.jobs.plot(ax=ax, style='b-')
df.rating.plot(ax=ax, style='r-', secondary_y=True)

plt.show()

looks like your database has entries for every day, while not every day has jobs, hence jobs/ratings values. To deal with this issue, you can either fill in placeholder values for the dates with no values through df.fillna(arguments) or drop the values df.dropna(inplace=True). If there are no non-observation data, it will connect the dots. — Uvar
– Uvar, Commented Mar 19, 2021 at 9:47
fillna didnt make any difference but the df.dropna(inplace=True) seems to worked perfectly. thankyou so much! :) — Kelly b
– Kelly b, Commented Mar 20, 2021 at 9:45

Florian Hall · Accepted Answer · 2021-03-19 09:46:39Z

3

I think you are looking for Dataframe.fillna().

df.fillna(method='ffill')

Forward Fill ('ffill') will use the last valid observation in place of a missing value.

answered Mar 19, 2021 at 9:46

Florian Hall

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Orozco · Accepted Answer · 2021-03-19 09:44:18Z

0

to fill your data you can use pandas fill.na and use 'method=ffill' to propagate the last valid value. Check the documentation to see what method fits best.

answered Mar 19, 2021 at 9:44

Orozco

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