Why is the code not plotting the expected output?

Question

country = str(input())

import matplotlib.pyplot as plt
lines = f.readlines ()
x = []
y = []
results = []    
for line in lines:       
  words = line.split(',')         
f.close()

plt.plot(x,y)
plt.show()

First problem is in the title of the plot. It is giving Population inCountryI instead of Population in Country I.

Second problem is in the graph.

Answer 1

While my answer could point out the mistakes in your code, I think it might also be enlightening to show another, perhaps more standard way, of doing this. This is particularly useful if you're going to do this more often, or with large datasets.

Handling CSV files and creating subgroups out of them by yourself is nice, but can become very tricky. Python already has a built-in csv module, but the Pandas library is nowadays basically the default (there are other options as well) for handling tabular data. Which means it is widely available, and/or easy to install. Plus it goes well with Matplotlib. (Read some of Pandas' user's guide for a good overview.)

With Pandas, you can use the following (I've put comments on the code in between the actual code):

import pandas as pd
import matplotlib.pyplot as plt
mpl.rcParams['figure.figsize'] = (8, 8)

# Read the CSV file into a Pandas dataframe
# For a normal CSV, this will work fine without tweaks
df = pd.read_csv('population.csv')

# Convert the month and year columns to a datetime
# Years have to be converted to string type for that
# '%b%Y' is the format for month abbrevation (English) and 4-digit year; 
# see e.g. https://strftime.org/
# Instead of creating a new column, we set the date as the index ("row-indices")
# of the dataframe
df.index = pd.to_datetime(df['Month'] + df['Year'].astype(str), format='%b%Y')

# We can remove the month and year columns now
df = df.drop(columns=['Month', 'Year'])

# For nicety, replace the dot in the country name with a space
df['Country'] = df['Country'].str.replace('.', ' ', regex=False)

# Group the dataframe by country, and loop over the groups
# The resulting grouped dataframes, `grouped`, will have just
# their index (date) values and population values
# The .plot() method will therefore automatically use 
# the index/dates as x-axis, and the population as 
# y-axis.
for country, grouped in df.groupby('Country'):

    # Use the convenience .plot() method
    grouped.plot()

    # Standard Matplotlib functions are still available
    plt.title(country)

The resulting plots are shown below (2, given the example data).

If you don't want a legend (since there is only one line), use grouped.plot(legend=None) instead.

If you want to pick one specific country, remove and replace the whole for-loop with the following

country = "Country II"
df[df['Country'] == country].plot()

If you want to do even more, also have a look at the Seaborn library.

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Resulting plots: