Python: Comparison of Reported and Estimated Total Damaged Rice Crop

Here I will show how to plot side-by-side bar with line graph to show the comparison of reported and estimated total damaged rice crop with the code written in Python Jupiter Notebook.

1. Data Table

Data source name: data_table.csv

Figure 1: Data table for total damaged rice crop plot.

2. Code

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import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from matplotlib import rc

# set font type
plt.rcParams["font.family"] = "Arial"

# import data table
df_crv = pd.read_csv('data_table.csv')

# assign values
x = np.arange(len(df_crv))
item = df_crv.iloc[:,0]
aff_ha = df_crv.iloc[:,1]
dm_ha = df_crv.iloc[:,2]
dm_er = df_crv.iloc[:,3]
dm_mr = df_crv.iloc[:,4]
dm_lr = df_crv.iloc[:,5]
dm_lr

# create plot
plt.figure(figsize=(8,5.5),constrained_layout=True) 
plt.rc('font', size=18)
plt.rc('xtick', labelsize=18)
plt.rc('ytick', labelsize=18)
plt.rc('axes', labelsize=20)
bw = 0.2

plt.bar(x, aff_ha,width = bw, color = 'grey', edgecolor = 'w', label='Total affected rice', zorder = 2,alpha = 0.8)
plt.bar(x+bw, dm_er,width = bw, color ='#2077B4', edgecolor = 'w', label='Damaged early rice',zorder = 2, alpha = 0.8)
plt.bar(x+bw+bw, dm_mr,width = bw, color = '#B22222', edgecolor = 'w', label='Damaged medium rice', zorder = 2,alpha = 0.8)
plt.bar(x+bw+bw+bw, dm_lr,width = bw, color = '#228B22', edgecolor = 'w', label='Damaged late rice', zorder = 2,alpha = 0.8)
plt.xticks(x+0.3, item)

plt.plot(x+0.3, dm_ha, color ='black', linestyle = '-', marker = 's', markersize = 9, label = 'Total damaged rice')

plt.ylim(0,50)
plt.grid(which='major',linestyle='--', axis = 'y')
plt.ylabel('Rice area [in thousand ha]', fontsize = 20)
plt.xlabel('Type of FDCs', fontsize = 20)
plt.legend(loc = 'upper center', ncol = 2)
plt.text(2.25,2.8 ,'Unable to estimate', fontsize = 18, rotation = 90, color = 'tab:red')

plt.savefig('stacked-bar-line.png', dpi = 300)
plt.show()

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3. Plot

Figure 2: Comparison of reported and estimated total damaged rice crop.

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Source code is available at: GitHub