Activity 13: Data Wrangling Task – Cleaning GDP Data
The GDP data is available on https://data.worldbank.org/ and it is available on GitHub at https://github.com/TrainingByPackt/Data-Wrangling-with-Python/blob/master/Chapter09/Activity12-15/India_World_Bank_Info.csv.
In this activity, we will clean the GDP data.
Create three DataFrames from the original DataFrame using filtering. Create the df_primary, df_secondary, and df_tertiary DataFrames for students enrolled in primary education, secondary education, and tertiary education in thousands, respectively.
Plot bar charts of the enrollment of primary students in a low-income country like India and a higher-income country like the USA.
Since there is missing data, use pandas imputation methods to impute these data points by simple linear interpolation between data points. To do that, create a DataFrame with missing values inserted and append a new DataFrame with missing values to the current DataFrame.
(For India) Append the rows corresponding...
