The script: (SAVE this below script with ".py" or ".ipynb" extensions) import pandas as pd import matplotlib.pyplot as plt import seaborn as sns import numpy as np sns.set() departure=pd.read_csv('file.csv') departure df = pd.DataFrame(departure, columns = ['year', 'var1', 'var2', 'var3']) print(df) plt.figure(figsize=(9,6)) pos = list(range(len(df['var1']))) width = 0.25 N=35 ind = np.arange(N) fig, ax = plt.subplots(figsize=(40,15)) plt.bar(pos, df['var1'], width, alpha=0.5, color='#059C1E') plt.bar([p + width for p in pos], df['var2'], width, alpha=0.5, color='#1032E0') plt.bar([p + width*2 for p in pos], df['var3'], width, alpha=0.5, color='#000000') ax.set_ylabel('Y-AXIS',fontweight='bold') plt.xlabel('Year', fontweight='bold') ax.set_title('Title') plt.xlim(min(pos)-width, max(pos)+width*4) plt.ylim([-42, max(df['var1'...