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Pandas First Steps
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Course Content

Pandas First Steps

Pandas First Steps

1. The Very First Steps
What is pandas? SeriesChallenge: Creating a SeriesDataFrameQuiz: Creating a SeriesQuiz: Creating a DataFrameAdding a New ColumnInserting a New ColumnDeleting a Row/Column Quiz: Matching the FunctionsWorking with ColumnsQuiz: Extracting Columnsiloc BasicsChallenge: Using iloc
2. Reading Files in Pandas
CSV FilesTXT FilesQuiz: Working with FilesQuiz: Accessing the Columns
3. Analyzing the Data
Viewing the DataQuiz: Using HeadQuiz: Head, Tail, and SampleExploring the DatasetColumn Names and Data TypesFinding Null ValuesQuiz: Identifying Null ValuesChallenge: Dropping Null ValuesChallenge: Filling Null ValuesQuiz: Null ValuesDescribing the Datamax() and min()Quiz: Statistical Operationssum() and count()Unique Values

book
Working with Columns

When working with a DataFrame, you can access each column individually.

python

To clarify this syntax:

  • Start by writing the name of the DataFrame you're working with;
  • Next, place the column name you want to access inside square brackets. Remember to enclose the column name in quotation marks.

Alternatively, you can use dot notation to access a column if the column name:

  1. Is a valid Python identifier (e.g., no spaces, special characters, or starting with a number);
  2. Does not conflict with an existing pandas attribute or method name.
python

              
12345678910111213

            
import pandas as pd

countries_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(countries_data)

capitals = countries['capital']

# Second option
# capitals = countries.capital

print(capitals)
copy

Executing this code will display just the column containing capital cities, rather than the entire DataFrame.

You can also access multiple columns like this:

python

Compared to accessing a single column, there is only one difference. This time, you'll need to put the list of column names inside an additional set of square brackets — meaning you'll use double square brackets.


              
12345678

            
import pandas as pd

countries_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(countries_data)
columns = countries[['country', 'capital']]
print(columns)
copy
Task

Swipe to start coding

You are given a DataFrame named audi_cars.

  • Retrieve the data for the columns 'model', 'year', and 'price' and store the result in the columns variable.

Solution

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Everything was clear?

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Thanks for your feedback!

Section 1. Chapter 11
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book
Working with Columns

When working with a DataFrame, you can access each column individually.

python

To clarify this syntax:

  • Start by writing the name of the DataFrame you're working with;
  • Next, place the column name you want to access inside square brackets. Remember to enclose the column name in quotation marks.

Alternatively, you can use dot notation to access a column if the column name:

  1. Is a valid Python identifier (e.g., no spaces, special characters, or starting with a number);
  2. Does not conflict with an existing pandas attribute or method name.
python

              
12345678910111213

            
import pandas as pd

countries_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(countries_data)

capitals = countries['capital']

# Second option
# capitals = countries.capital

print(capitals)
copy

Executing this code will display just the column containing capital cities, rather than the entire DataFrame.

You can also access multiple columns like this:

python

Compared to accessing a single column, there is only one difference. This time, you'll need to put the list of column names inside an additional set of square brackets — meaning you'll use double square brackets.


              
12345678

            
import pandas as pd

countries_data = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : ['Asia', 'Asia', 'Europe', 'Europe', 'Europe', 'South America', 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(countries_data)
columns = countries[['country', 'capital']]
print(columns)
copy
Task

Swipe to start coding

You are given a DataFrame named audi_cars.

  • Retrieve the data for the columns 'model', 'year', and 'price' and store the result in the columns variable.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 1. Chapter 11
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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