Assignment $3$

and python related. All questions are worth the same number of points except question $1$ which is worth $17\%$ of the assignment grade.

Note: Questions $2-13$ rely on your question $1$ answer.

$[]$: import pandas as pd

import numpy as np

# Filter all warnings. If you would like to see the warnings, please comment the two lines below.

import warnings

warnings.filterwarnings$(\text{'}$ignore$\text{'})$

Question $1$

$[\text{'}$Country$\text{'},$ 'Energy Supply', 'Energy Supply per Capita', $\text{'}\%$ Renewable$]$

Convert Energy Supply to gigajoules $($Note: there are $1,000,000$ gigajoules in a petajoule$).$ For all countries which have missing data $($e$.$g$.$ data with $"...")$ make sure this is reflected as np$.$ NaN values.

Rename the following list of countries $($for use in later questions$)$:

Next, load the GDP data from the file assets$/$world$\_$bank.csv$,$ which is a csv containing countries' GDP from $1960$ to $2015$ from World Bank. Call this DataFrame GDP$.$

Make sure to skip the header, and rename the following list of countries:

"Korea, Rep.": "South Korea", "Iran, Islamic Rep.": "Iran", "Hong Kong SAR, China": "Hong Kong"

$\text{'}2014\text{'},\text{'}2015\text{'}].$

This function should return a DataFrame with $20$ columns and $15$ entries, and the rows of the DataFrame should be sorted by "Rank".

def answer$\_$one$()$:

assert type$($answer$\_$one$())==$ pd$.$DataFrame, $"$Q$1$: You should return a DataFrame!"

assert answer$\_$one$().$shape $==(15,2),Q1$: Your DataFrame should have $20$ columns and $15$ entries!"