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select series of columns

nilotpalc answered on December 30, 2021 Popularity 3/10 Helpfulness 1/10

answer select series of columns

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select series of columns

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# Import pandas package
import pandas as pd
  
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'],
        'Age':[27, 24, 22, 32],
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj'],
        'Qualification':['Msc', 'MA', 'MCA', 'Phd']}
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data)
  
# iloc[row slicing, column slicing]
df.iloc [0:2, 1:3]

Popularity 3/10 Helpfulness 1/10 Language python

Source: www.geeksforgeeks.org

Tags: python select series

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Contributed on Dec 30 2021

nilotpalc

0 Answers Avg Quality 2/10

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select series of columns

Comment

# Import pandas package
import pandas as pd
  
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'],
        'Age':[27, 24, 22, 32],
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj'],
        'Qualification':['Msc', 'MA', 'MCA', 'Phd']}
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data)
  
# select all rows 
# and second to fourth column
df[df.columns[1:4]]

Popularity 1/10 Helpfulness 1/10 Language python

Source: www.geeksforgeeks.org

Tags: python select series

Link to this answer
Share Copy Link

Contributed on Dec 30 2021

nilotpalc

0 Answers Avg Quality 2/10

select series of columns

Comment

# Import pandas package
import pandas as pd
  
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'],
        'Age':[27, 24, 22, 32],
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj'],
        'Qualification':['Msc', 'MA', 'MCA', 'Phd']}
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data)
  
# Remember that Python does not
# slice inclusive of the ending index.
# select all rows 
# select first two column
df.iloc[:, 0:2]

Popularity 1/10 Helpfulness 1/10 Language python

Source: www.geeksforgeeks.org

Tags: select series python

Link to this answer
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Contributed on Dec 30 2021

nilotpalc

0 Answers Avg Quality 2/10

select series of columns

Comment

# Import pandas package
import pandas as pd
  
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'],
        'Age':[27, 24, 22, 32],
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj'],
        'Qualification':['Msc', 'MA', 'MCA', 'Phd']}
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data)
  
# select two rows and 
# column "name" to "Address"
# Means total three columns
df.loc[0:1, 'Name':'Address']

Popularity 1/10 Helpfulness 1/10 Language python

Source: www.geeksforgeeks.org

Tags: python series select

Link to this answer
Share Copy Link

Contributed on Dec 30 2021

nilotpalc

0 Answers Avg Quality 2/10

select series of columns

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