1.1 KiB
Exercise 2 Electric power consumption
The goal of this exercise is to learn to manipulate real data with Pandas.
The data set used is Individual household electric power consumption
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Delete the columns
Time,Sub_metering_2andSub_metering_3 -
Set
Dateas index -
Create a function that takes as input the DataFrame with the data set and returns a DataFrame with updated types:
def update_types(df): #TODO return df -
Use
describeto have an overview on the data set -
Delete the rows with missing values
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Modify
Sub_metering_1by adding 1 to it and multiplying the total by 0.06. If x is a row the output is: (x+1)*0.06 -
Select all the rows for which the Date is greater or equal than 2008-12-27 and
Voltageis greater or equal than 242 -
Print the 88888th row.
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What is the date for which the
Global_active_poweris maximal ? -
Sort the first three columns by descending order of
Global_active_powerand ascending order ofVoltage. -
Compute the daily average of
Global_active_power.