Removing duplicate records from CSV file using Python Pandas

Question

I would like to remove duplicate records from a csv file using Python Pandas
The CSV contains records with three attributes scale, minzoom, maxzoom. I want to have a resulting dataframe with minzoom and maxzoom and the records left being unique

i.e

Input CSV file (lookup_scales.csv)

 Scale, minzoom, maxzoom
 2000, 0, 15
 3000, 0, 15
 10000, 8, 15
 20000, 8, 15
 200000, 15, 18
 250000, 15, 18

Required distinct_lookup_scales.csv (Without scale column)

minzoom, maxzoom
0,5
8,15
15,18

My code so far is

lookup_scales_df = pd.read_csv('C:/Marine/lookup/lookup_scales.csv', names = ['minzoom','maxzoom'])
lookup_scales_df = lookup_scales_df.set_index([2, 3])
file_name = "C:/Marine/lookup/distinct_lookup_scales.csv"
lookup_scales_df.groupby('minzoom', 'maxzoom').to_csv(file_name, sep=',')

Very grateful for any help. I am new to pandas and working with dataframe

Asked By: daveb

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Source

Answer 1

You can use pd.read_csv(), pd.to_csv() and drop_duplicates():

import pandas as pd

df = pd.read_csv('test.csv', sep=', ', engine='python')

new_df = df[['minzoom','maxzoom']].drop_duplicates()

new_df.to_csv('out.csv', index=False)

Outputs to out.csv:

minzoom,maxzoom
0,15
8,15
15,18

Note sep=', ' when reading test.csv, otherwise your column names with contain a leading space if left with default sep=','.

Answered By: rahlf23

Answer 2

You don’t need numpy or anything you can just do the unique-ify in one line, while importing the csv using pandas:

import pandas as pd
df = pd.read_csv('lookup_scales.csv', usecols=['minzoom', 'maxzoom']).drop_duplicates(keep='first').reset_index()

output:

   minzoom  maxzoom
0        0       15
1        8       15
2       15       18

Then to write it out to csv:

df.to_csv(file_name, index=False) # you don't need to set sep in this because to_csv makes it comma delimited.

So the whole code:

import pandas as pd
df = pd.read_csv('lookup_scales.csv', usecols=['minzoom', 'maxzoom']).drop_duplicates(keep='first').reset_index()
file_name = "C:/Marine/lookup/distinct_lookup_scales.csv"
df.to_csv(file_name, index=False) # you don't need to set sep in this because to_csv makes it comma delimited.

Answered By: d_kennetz

Answer 3

The answer provided by d_kennetz is completely wrong. The correct way of doing this while keeping other columns intact is by replacing h:

df = pd.read_csv('yourcsvfilehere.csv').drop_duplicates('columnnamehere',keep='first')

Answered By: user380208

Answer 4

Here’s a simple Python script to do that. You’ll use Pandas which is a powerful data manipulation library.

import pandas as pd

# read CSV file
data = pd.read_csv('input.csv')

# remove duplicates based on 'email' column
cleaned_data = data.drop_duplicates(subset='email')

# save the cleaned data into a new CSV file
cleaned_data.to_csv('cleaned.csv', index=False)

Answered By: surya pratap singh

Removing duplicate records from CSV file using Python Pandas

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