如何在 Pandas 中更轻松地绘制此 DataFrame

Question

This is my DataFrame:

I plotted my df in Pandas with this code:

Armenia = [100.0,   21.943089,  23.344123]
Moldova = [100.0, 25.468598, 25.856620]
Ukraine =   [100.0, 45.253380, 26.266646]

Vietnam =   [100.0, 491.680706, 1083.782579]
Oman =  [100.0, 277.381353, 659.887243]
Bangladesh =    [100, 280.025959, 609.648111]


df = pd.DataFrame({'Vietnam' : Vietnam, 'Ukraine' : Ukraine, 'Bangladesh' : Bangladesh, 'Oman' : Oman,'Armenia': Armenia,'Moldova': Moldova}, index = ['1990', '2005', '2017'])

ax = df.plot.line(rot=0)

plt.title('Top 3 best and worst countries in combatting CO2 emission above 5 mt CO2', fontsize=14)
plt.xlabel('years', fontsize=14)
plt.ylabel('relative amount of CO2 emitted in %', fontsize=12)
plt.grid(True)

Output:

Is there any easier way to do this? Because it takes a lot of time to write all the data.

I really appreciate any comments. Thanks! :)

Answer 1

Your dataframe is in wide format so I changed it to long format using pd.melt ( docs )

I plotted the measurements using barplots since I thought you could see the evolution of CO2 emissions better like this.

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

dic = {'country' : ['Vietnam', 'Oman', 'Bangladesh', 'Ukraine', 'Moldova', 'Armenia'],
       'base' : [100.0, 100.0, 100.0, 100.0, 100.0, 100.0],
       'RA05' : [491, 277, 280, 45, 25, 21],
       'RA17' : [1083, 659, 609, 26, 25, 23]
      }

df = pd.DataFrame(dic)
df_melted = pd.melt(df, id_vars='country', value_name='Value', var_name='Measurement')
print(df_melted)

ax = sns.barplot(data=df_melted, x='country', y='Value', hue='Measurement')
ax.set(xlabel='Country', ylabel='Relative ammount of CO2 emitted in %', title='Top 3 best and worst countries in combatting CO2 emission above 5 mt CO2')
plt.show()

I'll update my answer once I figure out how to plot it with a line plot in pandas.