A Python module for processing CSV files efficiently
Project description
PythonCSVUtils
pythonCSVutils
is a lightweight Python library that provides utility functions for working with CSV files. It allows you to read, write, filter, sort, update, select, group, aggregate, merge, and manipulate CSV data with ease.
Installation
You can install pythonCSVutils via pip:
pip install pythonCSVutils
Usage
Import the necessary functions from the library:
from pythonCSVutils import read_csv, write_csv, filter_rows, sort_rows, update_rows, select_columns, read_csv_header, append_rows, group_by, aggregate, merge, drop_columns
#Reading and Writing CSV Files
data = read_csv('data.csv')
#Write data to a CSV file
write_csv('output.csv', data)
#Filter rows based on a condition
filtered_data = filter_rows(data, lambda row: row['age'] > 30)
#Sort rows based on a key
sorted_data = sort_rows(data, 'age', reverse=True)
#Update rows by modifying a specific column
updated_data = update_rows(data, 'age', lambda row: row['age'] + 1)
#Select specific columns from the data
selected_data = select_columns(data, ['name', 'age'])
#Read the header of a CSV file
header = read_csv_header('data.csv')
#Append rows to an existing CSV file
append_rows('data.csv', new_rows)
#Group data by a specific key
grouped_data = group_by(data, 'gender')
#Aggregate data based on a grouping key, an aggregation key, and an aggregation function
aggregated_data = aggregate(data, 'gender', 'age', sum)
#Merge two datasets based on a common key
merged_data = merge(data1, data2, 'id')
#Drop specific columns from the data
dropped_data = drop_columns(data, ['email', 'phone'])
License
This project is licensed under the MIT License.
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