Introduction

Welcome to the Learn Pandas track. These hands-on exercises are targeted for someone who has worked with Pandas a little before. Each page has a list of relevant resources you can use if you get stumped. The top item in each list has been custom-made to help you with the exercises on that page.

The first step in most data analytics projects is reading the data file. In this section, you'll create Series and DataFrame objects, both by hand and by reading data files.

Relevant Resources

Set Up

Run the code cell below to load libraries you will need (including coad to check your answers).

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import pandas as pd
pd.set_option('max_rows', 5)
from learntools.advanced_pandas.creating_reading_writing import *

Checking Answers

You can check your answers in each of the exercises that follow using the check_qN function provided in the code cell above (replacing N with the number of the exercise). For example here's how you would check an incorrect answer to exercise 1:

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check_q1(pd.DataFrame())

For the questions that follow, if you use check_qN on your answer, and your answer is right, a simple True value will be returned.

If you get stuck, you may run the print(answer_qN()) function to print the answer outright.

Exercises

Exercise 1: Create a DataFrame that looks like this:

In [ ]:
# Your code here

Exercise 2: Create the following DataFrame:

In [ ]:
# Your code here

Exercise 3: Create a Series that looks like this:

Flour     4 cups
Milk       1 cup
Eggs     2 large
Spam       1 can
Name: Dinner, dtype: object
In [ ]:
# Your code here

Exercise 4: Read the following csv dataset on wine reviews into the a DataFrame:

The filepath to the CSV file is ../input/wine-reviews/winemag-data_first150k.csv.

In [ ]:
# Your code here

Exercise 6**: Suppose we have the following DataFrame:

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q6_df = pd.DataFrame({'Cows': [12, 20], 'Goats': [22, 19]}, index=['Year 1', 'Year 2'])

Save this DataFrame to disc as a csv file with the name cows_and_goats.csv.

In [ ]:
# Your code here

Exercise 7: This exercise is optional. Read the following SQL data into a DataFrame:

The filepath is ../input/pitchfork-data/database.sqlite. Hint: use the sqlite3 library. The name of the table is artists.

In [ ]:
# Your Code Here

Keep going

Move on to the indexing, selecting and assigning workbook

This is part of the Learn Pandas series.