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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? SeriesCreating a SeriesDataFrameSeries QuizCreating a DataFrame QuizAdding a New ColumnInserting a New ColumnDeleting a Row/Column Matching the FunctionsWorking with ColumnsExtracting Columns Quiziloc BasicsUsing iloc
2. Reading Files in Pandas
CSV FilesTXT FilesWorking with Files QuizAccessing the Columns
3. Analyzing the Data
Viewing the DataHead QuizHead and Tail QuizInformation on the DataColumn Names and Data TypesFinding Null ValuesIdentifying Null Values QuizDropping Null ValuesFilling Null ValuesNull Values QuizDescribing the DataCalculating Descriptive Statisticsmax() and min()Statistical Operations Quizsum() and count()Unique Values

bookWorking with Columns

When working with a DataFrame, you can access each column individually. Here's the syntax for doing so:

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.

Let's look at an example using a DataFrame.


              
123456789

            
import pandas as pd

dataset = {'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(dataset)

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:

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. Check out the example below.


              
12345678

            
import pandas as pd

dataset = {'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(dataset)
columns = countries[['country', 'capital']]
print(columns)
copy

Task

Retrieve the columns 'model', 'year', and 'price' (in that order) from the audi_cars DataFrame. Give it a try!

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
toggle bottom row

bookWorking with Columns

When working with a DataFrame, you can access each column individually. Here's the syntax for doing so:

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.

Let's look at an example using a DataFrame.


              
123456789

            
import pandas as pd

dataset = {'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(dataset)

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:

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. Check out the example below.


              
12345678

            
import pandas as pd

dataset = {'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(dataset)
columns = countries[['country', 'capital']]
print(columns)
copy

Task

Retrieve the columns 'model', 'year', and 'price' (in that order) from the audi_cars DataFrame. Give it a try!

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
toggle bottom row

bookWorking with Columns

When working with a DataFrame, you can access each column individually. Here's the syntax for doing so:

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.

Let's look at an example using a DataFrame.


              
123456789

            
import pandas as pd

dataset = {'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(dataset)

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:

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. Check out the example below.


              
12345678

            
import pandas as pd

dataset = {'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(dataset)
columns = countries[['country', 'capital']]
print(columns)
copy

Task

Retrieve the columns 'model', 'year', and 'price' (in that order) from the audi_cars DataFrame. Give it a try!

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!

When working with a DataFrame, you can access each column individually. Here's the syntax for doing so:

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.

Let's look at an example using a DataFrame.


              
123456789

            
import pandas as pd

dataset = {'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(dataset)

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:

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. Check out the example below.


              
12345678

            
import pandas as pd

dataset = {'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(dataset)
columns = countries[['country', 'capital']]
print(columns)
copy

Task

Retrieve the columns 'model', 'year', and 'price' (in that order) from the audi_cars DataFrame. Give it a try!

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