line_plot.py

import numpy as np  # useful for many scientific computing in Python
import pandas as pd # primary data structure library

%matplotlib inline 

import matplotlib as mpl
import matplotlib.pyplot as plt

### type your answer here
df_CI = df_can.loc[['India', 'China'], years]
df_CI.index = df_CI.index.map(int) # let's change the index values of df_CI to type integer for plotting
df_CI.plot(kind='line')
plt.title('Immigrants from China and India')
plt.ylabel('Number of Immigrants')
plt.xlabel('Years')

plt.show()
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inplace = True # paramemter saves the changes to the original df_can dataframe
df_can.sort_values(by='Total', ascending=False, axis=0, inplace=True)

    # get the top 5 entries
df_top5 = df_can.head(5)

    # transpose the dataframe
df_top5 = df_top5[years].transpose() 

print(df_top5)


    #Step 2: Plot the dataframe. To make the plot more readeable, we will change the size using the `figsize` parameter.
df_top5.index = df_top5.index.map(int) # let's change the index values of df_top5 to type integer for plotting
df_top5.plot(kind='line', figsize=(14, 8)) # pass a tuple (x, y) size



plt.title('Immigration Trend of Top 5 Countries')
plt.ylabel('Number of Immigrants')
plt.xlabel('Years')


plt.show()