Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.Lære Accessing Elements from a Series | Getting Started
Pandas: First Steps

bookAccessing Elements from a Series

Default Indexing

We can access elements via their numerical (default) indices using the usual syntax series_name[index]:


              
12345678

            
import pandas as pd

temperatures = pd.Series(
  [22, 18, 25, 19]
)

# Access the 3rd element
print(temperatures[2])
copy

If the Series has Custom Indices, then it's recommended to use the iloc property for indexing:


              
123456789

            
import pandas as pd

temperatures = pd.Series(
    [22, 18, 25, 19],
    index=["Monday", "Tuesday", "Wednesday", "Thursday"]
)

# Accessing the 3rd element
print(temperatures.iloc[2])
copy

Custom Indexing

The syntax of Custom Indexing is very similar to accessing elements of a dictionary:


              
123456789

            
import pandas as pd

temperatures = pd.Series(
    [22, 18, 25, 19],
    index=["Monday", "Tuesday", "Wednesday", "Thursday"]
)

# Accessing the temperature on "Wednesday"
print(temperatures["Wednesday"])
copy

Slicing with Default Indices

We can slice a Series using the syntax:

series_name[start:end]

It's important to note that the in case of default indices, the end is exclusive, which can be better understood with the following example:


              
1234567891011

            
import pandas as pd

temperatures = pd.Series(
    [22, 18, 25, 19, 21, 23, 20],
    index=["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
)

# The index "6" is excluded
weekdays = temperatures.iloc[0:6]

print(weekdays)
copy

Slicing with Custom Indices

We can slice a series using it's custom indices too. In this case the syntax is the same as before, except the end element is also included in the slice:


              
1234567891011

            
import pandas as pd

temperatures = pd.Series(
    [22, 18, 25, 19, 21, 23, 20],
    index=["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
)

# "Friday" is included in the slice
weekdays = temperatures['Monday':'Friday']

print(weekdays)
copy

1. What will be the output of the following code?

2. Which method is recommended to access elements by position when using custom indices?

3. What is the output of this code?

question mark

What will be the output of the following code?

Select the correct answer

question mark

Which method is recommended to access elements by position when using custom indices?

Select the correct answer

question mark

What is the output of this code?

Select the correct answer

Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 1. Kapittel 5

Spør AI

expand

Spør AI

ChatGPT

Spør om hva du vil, eller prøv ett av de foreslåtte spørsmålene for å starte chatten vår

Suggested prompts:

Still meg spørsmål om dette emnet

Oppsummer dette kapittelet

Vis eksempler fra virkeligheten

Awesome!

Completion rate improved to 2.7

bookAccessing Elements from a Series

Sveip for å vise menyen

Default Indexing

We can access elements via their numerical (default) indices using the usual syntax series_name[index]:


              
12345678

            
import pandas as pd

temperatures = pd.Series(
  [22, 18, 25, 19]
)

# Access the 3rd element
print(temperatures[2])
copy

If the Series has Custom Indices, then it's recommended to use the iloc property for indexing:


              
123456789

            
import pandas as pd

temperatures = pd.Series(
    [22, 18, 25, 19],
    index=["Monday", "Tuesday", "Wednesday", "Thursday"]
)

# Accessing the 3rd element
print(temperatures.iloc[2])
copy

Custom Indexing

The syntax of Custom Indexing is very similar to accessing elements of a dictionary:


              
123456789

            
import pandas as pd

temperatures = pd.Series(
    [22, 18, 25, 19],
    index=["Monday", "Tuesday", "Wednesday", "Thursday"]
)

# Accessing the temperature on "Wednesday"
print(temperatures["Wednesday"])
copy

Slicing with Default Indices

We can slice a Series using the syntax:

series_name[start:end]

It's important to note that the in case of default indices, the end is exclusive, which can be better understood with the following example:


              
1234567891011

            
import pandas as pd

temperatures = pd.Series(
    [22, 18, 25, 19, 21, 23, 20],
    index=["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
)

# The index "6" is excluded
weekdays = temperatures.iloc[0:6]

print(weekdays)
copy

Slicing with Custom Indices

We can slice a series using it's custom indices too. In this case the syntax is the same as before, except the end element is also included in the slice:


              
1234567891011

            
import pandas as pd

temperatures = pd.Series(
    [22, 18, 25, 19, 21, 23, 20],
    index=["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
)

# "Friday" is included in the slice
weekdays = temperatures['Monday':'Friday']

print(weekdays)
copy

1. What will be the output of the following code?

2. Which method is recommended to access elements by position when using custom indices?

3. What is the output of this code?

question mark

What will be the output of the following code?

Select the correct answer

question mark

Which method is recommended to access elements by position when using custom indices?

Select the correct answer

question mark

What is the output of this code?

Select the correct answer

Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 1. Kapittel 5
some-alt