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This notebook is an exercise in the Pandas course. You can reference the tutorial at this link.


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

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

import pandas as pd
pd.set_option('max_rows', 5)
from learntools.core import binder; binder.bind(globals())
from learntools.pandas.creating_reading_and_writing import *
print("Setup complete.")
Setup complete.



In the cell below, create a DataFrame fruits that looks like this:

# Your code goes here. Create a dataframe matching the above diagram and assign it to the variable fruits.
fruits = pd.DataFrame({'Apples':[30], 'Bananas':[21]})

# Check your answer
<IPython.core.display.Javascript object>


Apples Bananas
0 30 21


Create a dataframe fruit_sales that matches the diagram below:

# Your code goes here. Create a dataframe matching the above diagram and assign it to the variable fruit_sales.
fruit_sales = pd.DataFrame({'Apples':[35, 41], 'Bananas':[21, 34]}, index=['2017 Sales', '2018 Sales'])

# Check your answer
<IPython.core.display.Javascript object>


Apples Bananas
2017 Sales 35 21
2018 Sales 41 34


Create a variable ingredients with a Series that looks like:

Flour     4 cups
Milk       1 cup
Eggs     2 large
Spam       1 can
Name: Dinner, dtype: object
ingredients = pd.Series(['4 cups', '1 cup', '2 large', '1 can'], index=['Flour', 'Milk', 'Eggs', 'Spam'], name='Dinner')

# Check your answer
<IPython.core.display.Javascript object>


Flour     4 cups
Milk       1 cup
Eggs     2 large
Spam       1 can
Name: Dinner, dtype: object


Read the following csv dataset of wine reviews into a DataFrame called reviews:

The filepath to the csv file is ../input/wine-reviews/winemag-data_first150k.csv. The first few lines look like:

0,US,"This tremendous 100% varietal wine[...]",Martha's Vineyard,96,235.0,California,Napa Valley,Napa,Cabernet Sauvignon,Heitz
1,Spain,"Ripe aromas of fig, blackberry and[...]",Carodorum Selección Especial Reserva,96,110.0,Northern Spain,Toro,,Tinta de Toro,Bodega Carmen Rodríguez
reviews = pd.read_csv("../input/wine-reviews/winemag-data_first150k.csv", index_col=0)

# Check your answer
<IPython.core.display.Javascript object>


country description designation points price province region_1 region_2 variety winery
0 US This tremendous 100% varietal wine hails from ... Martha's Vineyard 96 235.0 California Napa Valley Napa Cabernet Sauvignon Heitz
1 Spain Ripe aromas of fig, blackberry and cassis are ... Carodorum Selección Especial Reserva 96 110.0 Northern Spain Toro NaN Tinta de Toro Bodega Carmen Rodríguez
... ... ... ... ... ... ... ... ... ... ...
150928 France A perfect salmon shade, with scents of peaches... Grand Brut Rosé 90 52.0 Champagne Champagne NaN Champagne Blend Gosset
150929 Italy More Pinot Grigios should taste like this. A r... NaN 90 15.0 Northeastern Italy Alto Adige NaN Pinot Grigio Alois Lageder

150930 rows × 10 columns

<IPython.core.display.Javascript object>

Hint: Note that the csv file begins with an unnamed column of increasing integers. We want this to be used as the index. Check out the description of the index_col keyword argument in the docs for read_csv.


Run the cell below to create and display a DataFrame called animals:

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

In the cell below, write code to save this DataFrame to disk as a csv file with the name cows_and_goats.csv.

# Your code goes here
# Check your answer
<IPython.core.display.Javascript object>



Keep going

Move on to learn about indexing, selecting and assigning.

Have questions or comments? Visit the course discussion forum to chat with other learners.

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