fuzzymatcher | Record linking package that fuzzy matches two Python pandas | Data Manipulation library

by RobinL Python Version: 0.0.6 License: MIT

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | fuzzymatcher Summary

fuzzymatcher is a Python library typically used in Utilities, Data Manipulation applications. fuzzymatcher has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install fuzzymatcher' or download it from GitHub, PyPI.

Record linking package that fuzzy matches two Python pandas dataframes using sqlite3 fts4

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Quality

Security

License

Reuse

Support

fuzzymatcher has a low active ecosystem.

It has 179 star(s) with 30 fork(s). There are 9 watchers for this library.

It had no major release in the last 12 months.

There are 18 open issues and 20 have been closed. On average issues are closed in 90 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of fuzzymatcher is 0.0.6

Quality

fuzzymatcher has 0 bugs and 0 code smells.

Security

fuzzymatcher has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

fuzzymatcher code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

fuzzymatcher is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

fuzzymatcher releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

fuzzymatcher saves you 390 person hours of effort in developing the same functionality from scratch.

It has 928 lines of code, 85 functions and 19 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed fuzzymatcher and discovered the below as its top functions. This is intended to give you an instant insight into fuzzymatcher implemented functionality, and help decide if they suit your requirements.

Compute the score between two records
Compute the probability between two tokens
Calculate the probability matching the given tokens
Returns the probability for a given token
Returns a list of potential match ids for the given record
Add scores to the potential match score
Return True if there are enough matches the best match
Search the given token list
Adds dmetaphones to a column
Convert a list of tokens into doublemetaphones
Add data to the target table
Create a concatenation string from a token dictionary
Preprocess the data
Add a prefix to the dataframe
Check if two tokens are misspellings
Get misspellings for a given token
Returns a cleaned tokenised version of field_dict
Convert tokens to dmetrics

Get all kandi verified functions for this library.

fuzzymatcher Key Features

No Key Features are available at this moment for fuzzymatcher.

fuzzymatcher Examples and Code Snippets

No Code Snippets are available at this moment for fuzzymatcher.

Community Discussions

Trending Discussions on fuzzymatcher

Fuzzymatcher returns NaN for best_match_score

Why use both conda and pip?

OperationalError: no such module: fts4 ? Also No Extensions Available in SQLite in Python

Compare two date columns in pandas DataFrame to validate third column

QUESTION

Fuzzymatcher returns NaN for best_match_score

Asked 2021-Mar-21 at 20:29

I'm observing odd behaviour while performing fuzzy_left_join from fuzzymatcher library. Trying to join two df, left one with 5217 records and right one with 8734, the all records with best_match_score is 71 records, which seems really odd . To achieve better results I even remove all the numbers and left only alphabetical charachters for joining columns. In the merged table the id column from the right table is NaN, which is also strange result.

left table - column for join "amazon_s3_name". First item - limonig

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ANSWER

Answered 2021-Mar-21 at 20:29

You could give polyfuzz a try. Use the examples' setup, for example using TF-IDF or Bert, then run:

Source https://stackoverflow.com/questions/66619277

QUESTION

Why use both conda and pip?

Asked 2021-Feb-21 at 03:24

In this article, the author suggests the following

To install fuzzy matcher, I found it easier to conda install the dependencies (pandas, metaphone, fuzzywuzzy) then use pip to install fuzzymatcher. Given the computational burden of these algorithms you will want to use the compiled c components as much as possible and conda made that easiest for me.

Can someone explain why he is suggesting to use Conda to install dependencies and then use pip to install the actual package i.e fuzzymatcher? Why can't we just use Conda for both? Also, how do we know if we are using the compiled C packages as he suggested?

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ANSWER

Answered 2021-Feb-21 at 00:34

For the compiled C packages, you could import a package, see where it's located, and check the package itself to see what it imports. At some point, you would read into an import of a compiled module (.so extension on *nix). There's possibly an easier way, but that may depend on at what point in the import sequence of the package the compiled module is loaded.

Fuzzymatcher may not be available through Conda, or only an outdated version, or only a version that matches an outdated set of dependencies. Then you may end up with an out-of-date set of packages. Pip may have a more recent version of fuzzymatcher, and likely cares less (for better or worse) on the versions of various other packages in your environment. I'm not familiar with fuzzymatcher, so I can't give you an exact reason: you'd have to ask the author.

Note that the point of that paragraph, on installing the necessary packages with Conda, is that some packages require (C) libraries (not necessary compiled packages, though these will depend on these libraries) that may not be installed by default on your system. Conda will install these for you; Pip will not.

Source https://stackoverflow.com/questions/66297879

QUESTION

OperationalError: no such module: fts4 ? Also No Extensions Available in SQLite in Python

Asked 2020-Nov-02 at 07:14

I am trying to use fuzzymatcher, but when I run the code I get the following error:

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ANSWER

Answered 2020-Nov-02 at 07:14

These are the Steps I Followed & Extensions got enabled,

Source https://stackoverflow.com/questions/64586694

QUESTION

Compare two date columns in pandas DataFrame to validate third column

Asked 2020-Apr-20 at 21:36

Background info
I'm working on a DataFrame where I have successfully joined two different datasets of football players using fuzzymatcher. These datasets did not have keys for an exact match and instead had to be done by their names. An example match of the name column from two databases to merge as one is the following

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ANSWER

Answered 2020-Apr-20 at 21:28

IICU: Please Try np.where. Works as follows;

Source https://stackoverflow.com/questions/61332263

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install fuzzymatcher

You can install using 'pip install fuzzymatcher' or download it from GitHub, PyPI.
You can use fuzzymatcher like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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