pyplot: plot average curve for multiple graphs-CodePudding

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

CodePudding user response：

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.

CodePudding user response：

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)