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Drop rows or/and columns that have x% of NaNs

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RammaH83 answered on March 17, 2020 Popularity 4/10 Helpfulness 1/10

answer Drop rows or/and columns that have x% of NaNs

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Drop rows or/and columns that have x% of NaNs

Comment

import pandas as pd
import numpy as np

# Create a sample DataFrame with missing values
data = {
    'A': [1, 2, np.nan, 4, 5],
    'B': [1, 2, 3, np.nan, 5],
    'C': [1, 2, 3, 4, 5],
}

df = pd.DataFrame(data)

def clean_dataframe(df):
    # Drop rows with more than 80% NaN
    df = df.dropna(thresh=0.8 * df.shape[1], axis=0)
    
    # Drop columns with more than 30% NaN
    df = df.dropna(thresh=0.7 * df.shape[0], axis=1)
    
    return df

# Clean the DataFrame
cleaned_df = clean_dataframe(df)

# Display the original and cleaned DataFrames
print("Original DataFrame:")
print(df)

print("\nCleaned DataFrame:")
print(cleaned_df)

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Source: chat.openai.com

Tags: drop python rows

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Contributed on Oct 20 2023

RammaH83

0 Answers Avg Quality 2/10

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drop row if all values are nan

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df = df.dropna(axis = 0, how = 'all')

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Source: datascience.stackexchange.com

Tags: drop

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Contributed on Dec 04 2021

Tender Turtle

0 Answers Avg Quality 2/10

how to remove rows with nan in pandas

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df.dropna(subset=[columns],inplace=True)

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Source: Grepper

Tags: nan

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Contributed on May 26 2021

Hami yestia ta honi bro

0 Answers Avg Quality 2/10

drop if nan in column pandas

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df = df[df['EPS'].notna()]

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Source: Grepper

Tags: drop

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Contributed on Mar 17 2020

Hambo

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drop row if all values are nan

Comment

df.dropna(axis = 0, how = 'all', inplace = True)

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Source: datascience.stackexchange.com

Tags: drop

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Contributed on Dec 04 2021

Tender Turtle

0 Answers Avg Quality 2/10

remove rows or columns with NaN value

Comment

df.dropna()     #drop all rows that have any NaN values
df.dropna(how='all')

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Source: stackoverflow.com

Tags: nan

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Contributed on Aug 23 2020

Desert Trap

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pandas drop row with nan

Comment

import pandas as pd

df = pd.DataFrame({'values_1': ['700','ABC','500','XYZ','1200'],
                   'values_2': ['DDD','150','350','400','5000'] 
                   })

df = df.apply (pd.to_numeric, errors='coerce')
df = df.dropna()
df = df.reset_index(drop=True)

print (df)

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Source: datatofish.com

Tags: drop

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Contributed on Feb 16 2021

Euler's Good Eye

0 Answers Avg Quality 2/10

remove all rows where one ccolumns egale to nan

Comment

#remove in dataframe but no in the file
df = df[df['column'].notna()]

#remove in dataframe and in the file
df.dropna(subset=['EPS'], how='all', inplace=True)

Popularity 9/10 Helpfulness 7/10 Language python

Source: Grepper

Tags: nan python

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Contributed on Nov 27 2020

BlueMoon

0 Answers Avg Quality 2/10

drop row based on NaN value of a column

Comment

df = df.dropna(subset=['colA', 'colC'])

Popularity 9/10 Helpfulness 7/10 Language python

Source: Grepper

Tags: drop

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Contributed on May 19 2022

Chunxiao Wang

0 Answers Avg Quality 2/10

remove rows with nan in column pandas

Comment

df.dropna(subset=['EPS'], how='all', inplace=True)

Popularity 10/10 Helpfulness 7/10 Language python

Source: stackoverflow.com

Tags: nan

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Contributed on Jun 15 2022

Jittery Jay

0 Answers Avg Quality 2/10

pandas remove rows with nan

Comment

df = df.dropna(axis = 0)

Popularity 10/10 Helpfulness 7/10 Language python

Source: Grepper

Tags: nan

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Contributed on Jun 19 2022

Clumsy Capuchin

0 Answers Avg Quality 2/10

Drop rows or/and columns that have x% of NaNs

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Drop rows or/and columns that have x% of NaNs

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drop row if all values are nan

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