add visualization of k means clustering as excel format by beqakd · Pull Request #2104 · TheAlgorithms/Python

beqakd · 2020-06-12T12:57:04Z

Describe your change:

Add nice feature to convert Dataframe with clustering number in it to excel style format. It is easily readable and also has a lot of features in it to navigate through data.(like mean, mean_with_zero, median, max, min and etc.)

Add an algorithm? K mean clustering into excel style. #2102 K mean clustering into excel style. #2102

Checklist:

I have read CONTRIBUTING.md.
This pull request is all my own work -- I have not plagiarized.
I know that pull requests will not be merged if they fail the automated tests.
This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
All new Python files are placed inside an existing directory.
All filenames are in all lowercase characters with no spaces or dashes.
All functions and variable names follow Python naming conventions.
All function parameters and return values are annotated with Python type hints.

TravisBuddy · 2020-06-12T12:59:57Z

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TravisBuddy · 2020-06-12T16:18:47Z

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TravisBuddy · 2020-06-12T19:35:40Z

Hey @beqakd,
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beqakd · 2020-06-12T19:36:42Z

Error is not from my PR. Style changes fixed.

cclauss · 2020-06-17T19:26:59Z

machine_learning/k_means_clust.py

    plot_heterogeneity(heterogeneity, k)
+
+
+def ReportGenerator(df, ClusteringVariables, FillMissingReport=None):


Type hints? Doctests? Function and variable names need to be snake_case -- See CONTRIBUTING.md.

Typehints okey. but i cant write doctests. It returns pandas dataframe can you suggest me some ideas how i can do it? We can test manually to be sure that it works

Is it impossible to examine various elements of a dataframe to ensure that those elements contain expected values?

Its not but i wont be able to check all of them, but i will do good testing with different approaches. Thanks!

Just a few sanity checks will be good enough for our purposes. Thx.

cclauss · 2020-06-17T19:28:05Z

machine_learning/k_means_clust.py

+    """
+    Function generates easy-erading clustering report. It takes 2 arguments as an input:
+        DataFrame - dataframe with predicted cluester column;
+        FillMissingReport - dcitionary of rules how we are going to fill missing


Suggested change

FillMissingReport - dcitionary of rules how we are going to fill missing

FillMissingReport - dictionary of rules how we are going to fill missing

TravisBuddy · 2020-06-19T11:05:37Z

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TravisBuddy · 2020-06-19T11:12:15Z

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machine_learning/k_means_clust.py

Co-authored-by: Christian Clauss <cclauss@me.com>

machine_learning/k_means_clust.py

Co-authored-by: Christian Clauss <cclauss@me.com>

cclauss

Thanks for your work here!

beqakd · 2020-06-19T16:47:18Z

Thanks for your work here!

Thanks a lot!

…s#2104) * add visualization of kmneas clust as excel format * style changes * style changes * Add doctest and typehint! * style change * Update machine_learning/k_means_clust.py Co-authored-by: Christian Clauss <cclauss@me.com> * Update machine_learning/k_means_clust.py Co-authored-by: Christian Clauss <cclauss@me.com> Co-authored-by: Christian Clauss <cclauss@me.com>

add visualization of kmneas clust as excel format

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cclauss reviewed Jun 17, 2020

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Add doctest and typehint!

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style change

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Update machine_learning/k_means_clust.py

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Co-authored-by: Christian Clauss <cclauss@me.com>

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Update machine_learning/k_means_clust.py

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Co-authored-by: Christian Clauss <cclauss@me.com>

cclauss approved these changes Jun 19, 2020

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cclauss merged commit d034add into TheAlgorithms:master Jun 19, 2020

		plot_heterogeneity(heterogeneity, k)


		def ReportGenerator(df, ClusteringVariables, FillMissingReport=None):

	FillMissingReport - dcitionary of rules how we are going to fill missing
	FillMissingReport - dictionary of rules how we are going to fill missing

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Describe your change:

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TravisBuddy commented Jun 12, 2020

TravisBuddy Request Identifier: 9d0eb2c0-acac-11ea-8245-836d9da6cb4c

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TravisBuddy commented Jun 12, 2020

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TravisBuddy commented Jun 19, 2020

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beqakd commented Jun 19, 2020

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beqakd commented Jun 12, 2020 •

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cclauss Jun 17, 2020 •

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