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Introduction to pandas [track]
course content

Kursusindhold

Introduction to pandas [track]

Introduction to pandas [track]

1. Basics
What is pandas?SeriesIndexes and ValuesChallengeDataFramesIndexes and ColumnsChallenge
2. Reading and Exploring Data
Reading CSV FilesReading XLS/XLSX FilesExploring Data [1/3]ChallengeExploring Data [2/3]Exploring Data [3/3]Challenge
3. Accessing DataFrame Values
Accessing Specific ColumnsChallengeAccessing Specific RowsChallengeAccessing Rows and ColumnsAccessing using .loc[] [1/3]Accessing using .loc[] [2/3]Accessing using .loc[] [3/3]
4. Aggregate Functions
Number of ObservationsUnique ObservationsCounting ValuesChallengeSum and ProductMean and MedianChallengeMinimum and Maximum

book
Series

The simplest pandas object is Series - one-dimensional ndarray (numpy array) with axis labels.

To create a series in pandas, use pd.Series() method (capital S), passing list/array of values as the parameter.


              
123456

            
# Importing library
import pandas as pd

# Creating pandas series
ser = pd.Series([1000, 2500, 1700])
print(ser)
copy

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Sektion 1. Kapitel 2

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course content

Kursusindhold

Introduction to pandas [track]

Introduction to pandas [track]

1. Basics
What is pandas?SeriesIndexes and ValuesChallengeDataFramesIndexes and ColumnsChallenge
2. Reading and Exploring Data
Reading CSV FilesReading XLS/XLSX FilesExploring Data [1/3]ChallengeExploring Data [2/3]Exploring Data [3/3]Challenge
3. Accessing DataFrame Values
Accessing Specific ColumnsChallengeAccessing Specific RowsChallengeAccessing Rows and ColumnsAccessing using .loc[] [1/3]Accessing using .loc[] [2/3]Accessing using .loc[] [3/3]
4. Aggregate Functions
Number of ObservationsUnique ObservationsCounting ValuesChallengeSum and ProductMean and MedianChallengeMinimum and Maximum

book
Series

The simplest pandas object is Series - one-dimensional ndarray (numpy array) with axis labels.

To create a series in pandas, use pd.Series() method (capital S), passing list/array of values as the parameter.


              
123456

            
# Importing library
import pandas as pd

# Creating pandas series
ser = pd.Series([1000, 2500, 1700])
print(ser)
copy

Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 1. Kapitel 2
Vi beklager, at noget gik galt. Hvad skete der?
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