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We looked inside some of the posts by perennial-beginner and here's what we found interesting.
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Link
Example of doing tf-idf for Chinese in Python.
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Create a new column by applying function to existing column
df['new_column'] = df['column'].apply(lambda x: function(x))
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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.
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Logit function
From Essential Statistics for Data Scientists
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## 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)
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library(DataExplorer) plot_correlation(df)
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