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Term frequency–inverse document frequency for Chinese novel/documents implemented in python. - Jasonnor/tf-idf-python

Example of doing tf-idf for Chinese in Python.

#tf-idf #NLP #Chinese #Python #Github repo #Useful

Create a new column by applying function to existing column

df['new_column'] = df['column'].apply(lambda x: function(x))

#Python #Pandas #Data wrangling #Useful

Is it possible to use Stanford Parser in NLTK? (I am not talking about Stanford POS.)

Instead use the new nltk.parse.corenlp.CoreNLPParser API and NLTK v3.3.

The same instructions are given on the nltk Github repo: https://github.com/nltk/nltk/wiki/Stanford-CoreNLP-API-in-NLTK

Most recent version, published in 2018.

#NLP #Tokenizer #CoreNLP #NLTK #Stackoverflow #Useful #Python

Make a Shiny mobile app.

#Shiny #Useful

Logit function

From Essential Statistics for Data Scientists

#Statistics

## Import libraries library(ClustOfVar) library(PCAmixdata) library(dendextend) ## Split up continuous and categorical varibles split <- splitmix(PimaIndiansDiabetes2) X1 <- split$X.quanti X2 <- split$X.quali ## Hierarchical clustering tree <- hclustvar(X.quanti = X1, X.quali = X2) ## Evaluate the stability of each partition stability(tree, B=40) ## 60 bootstrap samples ## Plot dend <- tree %>% as.dendrogram %>% hang.dendrogram dend %>% color_branches(k=5) %>% color_labels(k=5) %>% plot(horiz=TRUE)

#ClustOfVar #R #Feature selection

library(DataExplorer) plot_correlation(df)

#Correlation plot #DataExplorer #R #Feature selection

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