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24 lines
1.1 KiB
24 lines
1.1 KiB
2 years ago
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# Exercise 2 **Electric power consumption**
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The goal of this exercise is to learn to manipulate real data with Pandas.
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The data set used is **Individual household electric power consumption**
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1. Delete the columns `Time`, `Sub_metering_2` and `Sub_metering_3`
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2. Set `Date` as index
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3. Create a function that takes as input the DataFrame with the data set and returns a DataFrame with updated types:
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```python
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def update_types(df):
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#TODO
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return df
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```
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4. Use `describe` to have an overview on the data set
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5. Delete the rows with missing values
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6. Modify `Sub_metering_1` by adding 1 to it and multiplying the total by 0.06. If x is a row the output is: (x+1)*0.06
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7. Select all the rows for which the Date is greater or equal than 2008-12-27 and `Voltage` is greater or equal than 242
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8. Print the 88888th row.
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9. What is the date for which the `Global_active_power` is maximal ?
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10. Sort the first three columns by descending order of `Global_active_power` and ascending order of `Voltage`.
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11. Compute the daily average of `Global_active_power`.
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