FAQ: Aggregates in Pandas - Calculating Column Statistics

Frequently Asked Questions Python FAQ
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This community-built FAQ covers the “Calculating Column Statistics” exercise from the lesson “Aggregates in Pandas”.

Paths and Courses
This exercise can be found in the following Codecademy content:

Data Science

Data Analysis with Pandas

FAQs on the exercise Calculating Column Statistics

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2

Hi,
how to download these csv files so that i can practics on the loacal system
thanks

3

can anyone guide me where to download these exercise file. mean csv files

4

there should be a folder/directory icon in the lesson:;

image

there you can open the csv file, from there you could copy paste the content. So far i know there isn’t a download functionality available.

1 Like
5

thanks for your quick response

6

Hey there. I’m wanting to take some notes on this. The cheatsheet for Data Analysis in Pandas doesn’t have the “common commands” and it’s not possible to copy them out because they are in this little scrolling box.

Is there reasoning behind why this lesson doesn’t have as much info in the cheatsheet or why it’s less accessible? Will it come up later again?

1 Like
7

The examples in this lesson show the results of printing a column of a DataFrame as being a list of values, e.g.

print(customers.age)
>> [23, 25, 31, 35, 35, 46, 62]

But when I print a column of a DataFrame I get an indexed series, e.g.

>>> df
    Name  Age
0  Bobby   25
1  Nigel   45
2  Monty   65
>>> print(df.Age)
0    25
1    45
2    65
Name: Age, dtype: int64

Any idea what causes this difference?

8

Hi, if you want it as a dataframe you should use

df[[“Age”]]

Check the difference between that an this one: df[“Age”]