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pandas dataframe apply

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Clean Cottonmouth answered on May 16, 2020 Popularity 10/10 Helpfulness 2/10

answer pandas dataframe apply

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pandas dataframe apply

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df = pd.DataFrame([[4, 9]] * 3, columns=['A', 'B'])
df.apply(np.sqrt)
#     A    B
#0  2.0  3.0
#1  2.0  3.0
#2  2.0  3.0

Popularity 10/10 Helpfulness 2/10 Language python

Source: Grepper

Tags: apply dataframe pandas python

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Contributed on Aug 02 2022

Clean Cottonmouth

0 Answers Avg Quality 2/10

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install typescript

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npm install -g typescript

Popularity 10/10 Helpfulness 10/10 Language typescript

Source: www.npmjs.com

Tags: typescript t

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Contributed on May 16 2020

Adorable Alligator

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install typescript

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Don't forget to use the dev flag!!!
Yarn:
yarn global add --dev typescript
NPM:
npm install -g --save-dev typescript

Popularity 10/10 Helpfulness 6/10 Language typescript

Source: Grepper

Tags: typescript t

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Contributed on Dec 13 2020

ProMikeSundays

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install typescript

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// Set Up TypeScript
npm install typescript @types/node --save-dev

// Initialize a TypeScript Configuration
npx tsc --init

Popularity 8/10 Helpfulness 4/10 Language typescript

Source: medium.com

Tags: typescript t

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Contributed on Jun 03 2024

sharjeelfaiq

0 Answers Avg Quality 2/10

apply function in pandas

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# to Add a lambda function which will increase the entry in each column by 3
df["column_name"] = df["column_name"].apply(lambda x:x+3)
 Eg:  df["MPG_City"] = df["MPG_City"].apply(lambda x: x+3)

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Tags: apply appl

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Contributed on Dec 09 2022

Unusual Unicorn

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install typescript

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npm install typescript @types/node --save-dev

Popularity 8/10 Helpfulness 3/10 Language typescript

Source: medium.com

Tags: typescript t

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Contributed on Jun 03 2024

sharjeelfaiq

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pandas apply

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import pandas as pd

s = pd.Series([1,2,3,4,5])
  
# adding 5 to each value
new = s.apply(lambda num : num + 5)
  
# printing elements of old and new series
print(s.head().values,"\n",new.head().values)
#  [1 2 3 4 5] 
#  [6 7 8 9 10]

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Contributed on Aug 02 2022

Clean Cottonmouth

0 Answers Avg Quality 2/10

pandas apply

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# This function doubles the input value
def double(x):
  return 2*x
 
# Apply this function to double every value in a specified column
df.column1 = df.column1.apply(double)
 
# Lambda functions can also be supplied to `apply()`
df.column2 = df.column2.apply(lambda x : 3*x)
 
# Applying to a row requires it to be called on the entire DataFrame
df['newColumn'] = df.apply(lambda row: 
  row['column1'] * 1.5 + row['column2'],
  axis=1
)

Popularity 10/10 Helpfulness 3/10 Language python

Source: www.codecademy.com

Tags: pandas-apply pandas-app

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Contributed on Aug 03 2023

Wide-eyed Wren

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install typescript

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npm install -D typescript

Popularity 5/10 Helpfulness 1/10 Language typescript

Source: www.npmjs.com

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Contributed on Oct 01 2024

Healthy Hare

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pandas apply

Comment

import pandas as pd
 
# Function to add
def add_values(row):
    return row['A'] + row['B'] + row['C']
 
def main():
    # Create a dictionary with three fields each
    data = {
        'A': [1, 2, 3],
        'B': [4, 5, 6],
        'C': [7, 8, 9]}
 
    # Convert the dictionary into DataFrame
    df = pd.DataFrame(data)
    print("Original DataFrame:\n", df)
 
    # Apply the user-defined function to every row
    df['add'] = df.apply(add_values, axis=1)
 
    print('\nAfter Applying Function: ')
    # Print the new DataFrame
    print(df)
 
if __name__ == '__main__':
    main()

Popularity 5/10 Helpfulness 1/10 Language python

Source: www.geeksforgeeks.org

Tags: pandas-apply python

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Contributed on Oct 02 2024

Innocent Iguana

0 Answers Avg Quality 2/10

pandas dataframe apply

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