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Pandas First Steps
course content

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

bookDeleting a Row/Column

At times, certain columns may not provide valuable information, making it advantageous to remove them. The pandas library offers the drop() method for this purpose. Let's delve into the function's syntax.

  • index: Specifies the row indexes to be deleted (used when axis=0);
  • columns: Identifies the column names to be deleted (used when axis=1);
  • axis: Choose whether to remove labels from the rows (0) or columns (1). The default is 0.

In this section, we're going to work with a specific DataFrame. Let's examine it.


              
1234567

            
import pandas as pd 

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(dataset)
print(countries)
copy

We notice that the continent column contains numerous empty rows, making it less informative. Consequently, we'll remove it.


              
12345678

            
import pandas

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pandas.DataFrame(dataset)
countries = countries.drop(columns = ['continent'],axis=1)
print(countries)
copy

Time for some hands-on practice.

Task

We have a DataFrame called audi_cars. Take a close look at the provided dictionary and eliminate the irrelevant column. 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 9
toggle bottom row

bookDeleting a Row/Column

At times, certain columns may not provide valuable information, making it advantageous to remove them. The pandas library offers the drop() method for this purpose. Let's delve into the function's syntax.

  • index: Specifies the row indexes to be deleted (used when axis=0);
  • columns: Identifies the column names to be deleted (used when axis=1);
  • axis: Choose whether to remove labels from the rows (0) or columns (1). The default is 0.

In this section, we're going to work with a specific DataFrame. Let's examine it.


              
1234567

            
import pandas as pd 

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(dataset)
print(countries)
copy

We notice that the continent column contains numerous empty rows, making it less informative. Consequently, we'll remove it.


              
12345678

            
import pandas

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pandas.DataFrame(dataset)
countries = countries.drop(columns = ['continent'],axis=1)
print(countries)
copy

Time for some hands-on practice.

Task

We have a DataFrame called audi_cars. Take a close look at the provided dictionary and eliminate the irrelevant column. 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 9
toggle bottom row

bookDeleting a Row/Column

At times, certain columns may not provide valuable information, making it advantageous to remove them. The pandas library offers the drop() method for this purpose. Let's delve into the function's syntax.

  • index: Specifies the row indexes to be deleted (used when axis=0);
  • columns: Identifies the column names to be deleted (used when axis=1);
  • axis: Choose whether to remove labels from the rows (0) or columns (1). The default is 0.

In this section, we're going to work with a specific DataFrame. Let's examine it.


              
1234567

            
import pandas as pd 

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(dataset)
print(countries)
copy

We notice that the continent column contains numerous empty rows, making it less informative. Consequently, we'll remove it.


              
12345678

            
import pandas

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pandas.DataFrame(dataset)
countries = countries.drop(columns = ['continent'],axis=1)
print(countries)
copy

Time for some hands-on practice.

Task

We have a DataFrame called audi_cars. Take a close look at the provided dictionary and eliminate the irrelevant column. 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!

At times, certain columns may not provide valuable information, making it advantageous to remove them. The pandas library offers the drop() method for this purpose. Let's delve into the function's syntax.

  • index: Specifies the row indexes to be deleted (used when axis=0);
  • columns: Identifies the column names to be deleted (used when axis=1);
  • axis: Choose whether to remove labels from the rows (0) or columns (1). The default is 0.

In this section, we're going to work with a specific DataFrame. Let's examine it.


              
1234567

            
import pandas as pd 

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pd.DataFrame(dataset)
print(countries)
copy

We notice that the continent column contains numerous empty rows, making it less informative. Consequently, we'll remove it.


              
12345678

            
import pandas

dataset = {'country' : ['Thailand', 'Philippines', 'Monaco', 'Malta', 'Sweden', 'Paraguay', 'Latvia'],
          'continent' : [None, None, 'Europe', None, 'Europe', None, 'Europe'],
          'capital':['Bangkok', 'Manila', 'Monaco', 'Valletta', 'Stockholm', 'Asuncion', 'Riga']}
countries = pandas.DataFrame(dataset)
countries = countries.drop(columns = ['continent'],axis=1)
print(countries)
copy

Time for some hands-on practice.

Task

We have a DataFrame called audi_cars. Take a close look at the provided dictionary and eliminate the irrelevant column. 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 9
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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