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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

bookDataFrame

Series is the simplest data structure in pandas. Now let's delve into a more complex data structure: DataFrame. This is a two-dimensional object that is more commonly used.

Think of a DataFrame as akin to a spreadsheet, capable of containing large volumes of data. Like a spreadsheet, a DataFrame comes with an index and columns.

To create a DataFrame object, you'll need to use a dictionary in conjunction with the .DataFrame() function. Let's examine how the coding is executed.


              
123456

            
import pandas as pd
dataset = {'name' : ['Ann', 'Alex', 'Kevin', 'Kate'], 
          'age' : [35, 12, 24, 45]}

data_frame = pd.DataFrame(dataset)
print(data_frame)
copy

Task

Let's craft an animal DataFrame using the dataset data and the pd.DataFrame() function. 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 4
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bookDataFrame

Series is the simplest data structure in pandas. Now let's delve into a more complex data structure: DataFrame. This is a two-dimensional object that is more commonly used.

Think of a DataFrame as akin to a spreadsheet, capable of containing large volumes of data. Like a spreadsheet, a DataFrame comes with an index and columns.

To create a DataFrame object, you'll need to use a dictionary in conjunction with the .DataFrame() function. Let's examine how the coding is executed.


              
123456

            
import pandas as pd
dataset = {'name' : ['Ann', 'Alex', 'Kevin', 'Kate'], 
          'age' : [35, 12, 24, 45]}

data_frame = pd.DataFrame(dataset)
print(data_frame)
copy

Task

Let's craft an animal DataFrame using the dataset data and the pd.DataFrame() function. 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 4
toggle bottom row

bookDataFrame

Series is the simplest data structure in pandas. Now let's delve into a more complex data structure: DataFrame. This is a two-dimensional object that is more commonly used.

Think of a DataFrame as akin to a spreadsheet, capable of containing large volumes of data. Like a spreadsheet, a DataFrame comes with an index and columns.

To create a DataFrame object, you'll need to use a dictionary in conjunction with the .DataFrame() function. Let's examine how the coding is executed.


              
123456

            
import pandas as pd
dataset = {'name' : ['Ann', 'Alex', 'Kevin', 'Kate'], 
          'age' : [35, 12, 24, 45]}

data_frame = pd.DataFrame(dataset)
print(data_frame)
copy

Task

Let's craft an animal DataFrame using the dataset data and the pd.DataFrame() function. 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!

Series is the simplest data structure in pandas. Now let's delve into a more complex data structure: DataFrame. This is a two-dimensional object that is more commonly used.

Think of a DataFrame as akin to a spreadsheet, capable of containing large volumes of data. Like a spreadsheet, a DataFrame comes with an index and columns.

To create a DataFrame object, you'll need to use a dictionary in conjunction with the .DataFrame() function. Let's examine how the coding is executed.


              
123456

            
import pandas as pd
dataset = {'name' : ['Ann', 'Alex', 'Kevin', 'Kate'], 
          'age' : [35, 12, 24, 45]}

data_frame = pd.DataFrame(dataset)
print(data_frame)
copy

Task

Let's craft an animal DataFrame using the dataset data and the pd.DataFrame() function. 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 4
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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