Pandas lab Marco

[marcoayora]

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[sh-ih]

You’ll dream of pandas at the end of this bootcamp! Congrats on a very good lab

Some comments:
On question 6. Create a subset of this data frame that contains only the Score 1, 3, and 5 columns, the instruction was referring to the name of the columns, not the index, so the code should be:
subset_df = df[['Score_1','Score_3', 'Score_5']]

On question 12 you got the most and least expensive products, but you didn’t print the difference

On the exercises with the admissions dataframe, on question 2, you did the set_index, but since you didn’t use inplace=True as parameter, you can see that in the next question, your index is not Serial No. anymore.

On question 3 we had two conditions to meet: “number of rows where the CGPA is greater than 9 and the student has performed an investigation.” So you needed to run both conditions at the same time:

rslt = admissions[(admissions['CGPA'] > 9) & (admissions['Research'] > 0)]
rslt

And the same on question 4: “all the rows where the CGPA is greater than 9 and the SOP score is less than 3.5”:

rslt_4 =  admissions[(admissions["CGPA"]> 9) & (admissions["SOP"] < 3.5)]
rslt_4

And then calculate the mean of the Chance to admit column
mean_chance = rslt_4[‘Chance of Admit’].mean()