CleverCSV | Python package for handling messy CSV files | CSV Processing library
kandi X-RAY | CleverCSV Summary
kandi X-RAY | CleverCSV Summary
CleverCSV is a Python package that aims to solve some of the pain points of CSV files, while maintaining many of the good things. The package automatically detects (with high accuracy) the format (dialect) of CSV files, thus making it easier to simply point to a CSV file and load it, without the need for human inspection. In the future, we hope to solve some of the other issues of CSV files too. CleverCSV is based on science. We investigated thousands of real-world CSV files to find a robust way to automatically detect the dialect of a file. This may seem like an easy problem, but to a computer a CSV file is simply a long string, and every dialect will give you some table. In CleverCSV we use a technique based on the patterns of row lengths of the parsed file and the data type of the resulting cells. With our method we achieve 97% accuracy for dialect detection, with a 21% improvement on non-standard (messy) CSV files compared to the Python standard library.
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Top functions reviewed by kandi - BETA
- Implements the command line interface
- Import an optional optional dependency module
- Write the csv to a file
- Detect dialect
- Parse an integer
- Import optional dependency
- Read dicts from file
- Detect the dialect of the given data
- Stream data from a file
- Detect the dialect of the given sample
- Read data from file
- Write a table to a file
- Process csv files
- Write a list of dictionaries to a file
- Handles the command line
- Run dialect detection
- Create a csv dialect Dialect object
- Create a simple dialect object
- Calls pypi
- Check if cell is a currency
- Generate known types
- Build an application
- Run actions
- Commit changelog
- Clears a pre - release
- Activate command
- Build the man page
CleverCSV Key Features
CleverCSV Examples and Code Snippets
import csv
with open('input.csv', 'r', newline='') as input_file, open('output.csv','w', newline='') as output_file:
reader = csv.reader(input_file)
writer = csv.writer(output_file)
for line_number, row in enumerate(reader, s
Community Discussions
Trending Discussions on CleverCSV
QUESTION
Bit of an involved setup to this question, but bear with me!
(Copy and pasting the below block into an editor works well)
I am using clevercsv to load my data from a financial website's csv file. Each row is stored as an item in a list.
data = clevercsv.wrappers.read_csv(in_file_name)
After some account info lines, the stock data begins:
stock_data = data[8:]
I wish to remove the data: Market, Loan Value - all the way to - Day High (inclusive0
And Keep Symbol, Description -> % of Positions (inclusive), 52-wk Low, 52-wk High
Each stock has this data associated with it on the relevant line. Any best practices for removing this data? I have been trying and seem to be having logic errors.
As of Date,2020-04-29 18:44:29
Account,TD Direct Investing - HAHAHA
Cash,123.12
Investments,1234.12
Total Value,12345.12
Margin,123456.12,
,
Symbol,Market,Description,Quantity,Average Cost,Price,Book Cost,Market Value,Unrealized $,Unrealized %,% of Positions,Loan Value,Change Today $,Change Today %,Bid,Bid Lots,Ask,Ask Lots,Volume,Day Low,Day High,52-wk Low,52-wk High
AFL,US,"AFLAC INC",500,43.79,39.23,21895.79,19615.00,-2280.79,-10.42,7.26,,1.4399986,3.81,39.19,1,40.2,1,3001288,38.31,39.48,23.07,57.18
AKTS,US,"AKOUSTIS TECHNOLOGIES INC",2500,5.04,8.94,12609.87,22350.00,9740.13,77.24,8.27,,0.35999966,4.20,8.68,1,9.2,10,1161566,8.65,9.25,3.76,9.25
And here is my code so far:
...ANSWER
Answered 2020-Apr-30 at 00:58If you already know the column indices and the header length, you can do something like this:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install CleverCSV
CleverCSV is available on PyPI. You can install either the full version, which includes the command line interface and all optional dependencies, using. or you can install a lighter, core version of CleverCSV with.
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