pyplot: plot average curve for multiple graphs

Question

I'm a beginner in matplotlib. I've already created some graphs from a dataframe. Now I want to create the average graph from multiple graphs.

Can anyone help me with this?

My graphs look like this:

alb = df[df.location == 'Albania']
bel = df[df.location == 'Belarus']
bih = df[df.location == 'Bosnia and Herzegovina']
blg = df[df.location == 'Bulgaria']
cro = df[df.location == 'Croatia']
hun = df[df.location == 'Hungary']
kos = df[df.location == 'Kosovo']
mld = df[df.location == 'Moldova']
mng = df[df.location == 'Montenegro']
nmc = df[df.location == 'North Macedonia']
pol = df[df.location == 'Poland']
rom = df[df.location == 'Romania']
rus = df[df.location == 'Russia']
srb = df[df.location == 'Serbia']
tur = df[df.location == 'Turkey']
ukr = df[df.location == 'Ukraine']

plt.plot(alb.date, alb.new_deaths_per_million)
plt.plot(bel.date, bel.new_deaths_per_million)
plt.plot(bih.date, bih.new_deaths_per_million)
plt.plot(blg.date, blg.new_deaths_per_million)
plt.plot(cro.date, cro.new_deaths_per_million)
plt.plot(hun.date, hun.new_deaths_per_million)
plt.plot(kos.date, kos.new_deaths_per_million)
plt.plot(mld.date, mld.new_deaths_per_million)
plt.plot(mng.date, mng.new_deaths_per_million)
plt.plot(nmc.date, nmc.new_deaths_per_million)
plt.plot(pol.date, pol.new_deaths_per_million)
plt.plot(rom.date, rom.new_deaths_per_million)
plt.plot(rus.date, rus.new_deaths_per_million)
plt.plot(srb.date, srb.new_deaths_per_million)
plt.plot(tur.date, tur.new_deaths_per_million)
plt.plot(ukr.date, ukr.new_deaths_per_million)
plt.legend(['Albania', 'Belarus', 'Bosnia and Herzegovina', 'Bulgaria', 'Croatia', 'Hungary', 'Kosovo', 'Moldova', 'Montenegro', 'North Macedonia', 'Poland', 'Romania', 'Russia', 'Serbia', 'Turkey', 'Ukraine'])
plt.rcParams['figure.figsize'] = [12, 8]
plt.rcParams['figure.dpi'] = 200
plt.show()

The graphs look like this:

Now I would like to create the average curve from all these graphs. How can this be done?

Thanks for the help

This is the dataset I use:

url = 'https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/owid-covid-data.csv'
df = pd.read_csv(url,error_bad_lines=False)
pd.options.display.max_columns = None
display(df)

Answer 1

countries = ['Albania', 'Croatia', 'Hungary']  # fill in the missing countries
for country in countries:
  df_country = df[df.location == country]
  plt.plot(df_country.date, df_country.new_deaths_per_million)

df_countries = df[df.location.isin(countries)]
plt.plot(df_countries.date, df_countries.new_deaths_per_million.groupby('date').mean())

• Put your countries in an array, it makes your life easier, your code shorter and easier to maintain
• Then group your data by date and calculate the mean. The mean values can the be plotted.