Python and R data analysis/mining tools Mutual Search

If you are already familiar with the Python and R module/package loading method, the table below is relatively easy to find. Python is referenced in the following table as a module., and some modules are not native modules, please use

pip install *

installation; In the same vein, in order to facilitate indexing, R also::represents the function and the name of the package in which the function is located, if it does not contain a::default package that is represented as R,::please use

install.packages("*")

Installation.

Connector and IO database

category	Python	R
Mysql	Mysql-connector-python (official)	Rmysql
Oracle	Cx_oracle	Roracle
Redis	Redis	Rredis
Mongodb	Pymongo	Rmongo, Rmongodb
Neo4j	Py2neo	Rneo4j
Cassandra	Cassandra-driver	Rjdbc
Odbc	Pyodbc	RODBC
Jdbc	Unknown [Jython only]	Rjdbc

Io class

category	Python	R
Excel	Xlsxwriter, Pandas. (from/to) _excel, OPENPYXL	OPENXLSX::READ.XLSX (2), XLSX::READ.XLSX (2)
Csv	Csv.writer	Read.csv (2), read.table
Json	Json	Jsonlite
Image	PIL	JPEG, PNG, TIFF, BMP

Descriptive statistics of statistical classes

category	Python	R
Summary of Descriptive statistics	Scipy.stats.descirbe	Summary
Mean value	Scipy.stats.gmean (geometric mean), Scipy.stats.hmean (harmonic average), Numpy.mean, Numpy.nanmean, pandas. Series.mean	Mean
Number of Median	Numpy.median, Numpy.nanmediam, pandas. Series.median	Median
The majority of	Scipy.stats.mode, Pandas. Series.mode	Unknown
Number of Bits	Numpy.percentile, Numpy.nanpercentile, pandas. Series.quantile	Quantile
Cumulative experience Function (ECDF)	Statsmodels.tools.ECDF	Ecdf
Standard deviation	SCIPY.STATS.STD, SCIPY.STATS.NANSTD, NUMPY.STD, pandas. Series.std	Sd
Variance	Numpy.var, Pandas. Series.var	Var
Coefficient	Scipy.stats.variation	Unknown
Covariance	Numpy.cov, Pandas. Series.cov	CoV
(Pearson) Correlation coefficient	Scipy.stats.pearsonr, Numpy.corrcoef, pandas. Series.corr	Cor
Peak degree	Scipy.stats.kurtosis, Pandas. Series.kurt	E1071::kurtosis
Degree of skewness	Scipy.stats.skew, Pandas. Series.skew	E1071::skewness
Histogram	Numpy.histogram, numpy.histogram2d, NUMPY.HISTOGRAMDD	Unknown

Regression (including statistics and machine learning)

category	Python	R
Common least squares regression (OLS)	Statsmodels.ols, Sklearn.linear_model. Linearregression	Lm
Generalized linear regression (GLS)	Statsmodels.gls	Nlme::gls, Mass::gls
Scale regression (Quantile regress)	Statsmodels. Quantreg	Quantreg::rq
Ridge return	Sklearn.linear_model. Ridge	Mass::lm.ridge, Ridge::linearridge
LASSO	Sklearn.linear_model. Lasso	Lars::lars
Minimum angle regression	Sklearn.linear_modle. Lassolars	Lars::lars
Robust regression	Statsmodels. RLM	Mass::rlm

Hypothesis Testing

category	Python	R
T test	Statsmodels.stats.ttest_ind, Statsmodels.stats.ttost_ind, statsmodels.stats.ttost.paired; Scipy.stats.ttest_1samp, Scipy.stats.ttest_ind, Scipy.stats.ttest_ind_from_stats, Scipy.stats.ttest_rel	T.test
KS Test (test distribution)	Scipy.stats.kstest, Scipy.stats.kstest_2samp	Ks.test
Wilcoxon (non-parametric test, differential test)	Scipy.stats.wilcoxon, Scipy.stats.mannwhitneyu	Wilcox.test
Shapiro-wilk test of normal condition	Scipy.stats.shapiro	Shapiro.test
Pearson correlation coefficient test	Scipy.stats.pearsonr	Cor.test

Time series

category	Python	R
Ar	Statsmodels.ar_model.AR	Ar
Arima	Statsmodels.arima_model.arima	Arima
Var	Statsmodels.var_model.var	Unknown

Python can also be found inPyFlux.

Survival analysis

category	Python	R
ph regression	Statsmodels.formula.api.phreg	Unknown

Modules specifically analyzed:
Python:Lifelines

Machine Learning class Regression

See Statistical classes

Classifier LDA, QDA

category	Python	R
Lda	Sklearn.discriminant_analysis. Lineardiscriminantanalysis	Mass::lda
QDA	Sklearn.discriminant_analysis. Quadraticdiscriminantanalysis	Mass::qda

SVM (Support vector machine)

category	Python	R
Support Vector Classifier (SVC)	Sklearn.svm.SVC	E1071::svm
Non-support vector classifier (NONSVC)	Sklearn.svm.NuSVC	Unknown
Linear support vector classifier (lenear SVC)	Sklearn.svm.LinearSVC	Unknown

Based on proximity

category	Python	R
K-Nearest classifier	Sklearn.neighbors.KNeighborsClassifier	Unknown
Radius near classifier	Sklearn.neighbors.RadiusNeighborsClassifier	Unknown
Near center of gravity classifier (Nearest centroid Classifier)	Sklearn.neighbors.NearestCentroid	Unknown

Bayesian

category	Python	R
Naive Bayesian	Sklearn.naive_bayes. Gaussiannb	E1071::naivebayes
Dovibeyes (multinomial Naive Bayes)	Sklearn.naive_bayes. Multinomialnb	Unknown
Bernoulibeyes (Bernoulli Naive Bayes)	Sklearn.naive_bayes. Bernoullinb	Unknown

Decision Tree

category	Python	R
Decision Tree Classifier	Sklearn.tree.DecisionTreeClassifier	Tree::tree, Party::ctree
Decision Tree Regression	Sklearn.tree.DecisionTreeRegressor	Tree::tree, Party::tree

Assemble method

category	Sub-category	Python	R
Bagging	Random Forest classifier	Sklearn.ensemble.RandomForestClassifier	Randomforest::randomforest, Party::cforest
Bagging	Random Forest regression device	Sklearn.ensemble.RandomForestRegressor	Randomforest::randomforest, Party::cforest
Boosting	Gradient boosting	xgboostModule	xgboostPackage
Boosting	AdaBoost	Sklearn.ensemble.AdaBoostClassifier	adabag,fastAdaboost,ada
Stacking	Unknown	Unknown	Unknown

Clustering

category	Python	R
Kmeans	Scipy.cluster.kmeans.kmeans	Kmeans::kmeans
Hierarchical clustering	Scipy.cluster.hierarchy.fcluster	(Stats::) hclust
Baouzu class (Bagged Cluster)	Unknown	E1071::bclust
DBSCAN	Sklearn.cluster.DBSCAN	Dbscan::d Bsan
Birch	Sklearn.cluster.Birch	Unknown
K-medoids Clustering	Pyclust. Kmedoids (Reliability unknown)	Cluster.pam

Association Rules

category	Python	R
Apriori algorithm	Apriori (Unknown reliability, py3 not supported), Pyfim (Reliability unknown, PIP installation not available)	Arules::apriori
Fp-growth algorithm	Fp-growth (Unknown reliability, py3 not supported), Pyfim (Reliability unknown, PIP installation not available)	Unknown

Neural network

category	Python	R
Neural network	Neurolab.net, keras.*	Nnet::nnet, Nueralnet::nueralnet
Deep learning	keras.*	Unreliable packages mostly and unknown

Of course, thetheanomodule is worth mentioning, buttheanothe design of the essence package is not in the neural network, so it is not attributed to this class.

Probabilistic graph model

Python:PyMC3

Text, NLP basic operations

category	Python	R
Tokenize	Nltk.tokenize (UK), Jieba.tokenize (middle)	Tau::tokenize
Stem	Nltk.stem	Rtexttools::wordstem, Snowballc::wordstem
Stopwords	Stop_words.get_stop_words	Tm::stopwords, Qdap::stopwords
Chinese participle	Jieba.cut, Smallseg, Yaha, finalseg, genius	Jiebar
TFIDF	Gensim.models.TfidfModel	Unknown

Topic model

category	Python	R
Lda	Lda. LDA, Gensim.models.ldamodel.LdaModel	Topicmodels::lda
Lsi	Gensim.models.lsiModel.LsiModel	Unknown
Rp	Gensim.models.rpmodel.RpModel	Unknown
HDP	Gensim.models.hdpmodel.HdpModel	Unknown

It's worth noting that Python's new third-party modulespaCy

Interaction with other analysis/visualization/mining/reporting tools

category	Python	R
Weka	Python-weka-wrapper	Rweka
Tableau	Tableausdk	Rserve (actual service pack for R)

Reproduced in: 1190000005041649

Python and R data analysis/mining tools Mutual Search