Must Know Packages For a Successful Data Scientist
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Must Know Packages For a Successful Data Scientist

 

Packages For Data Manipulation
Must know Packages for a successful Data Scientist
Packages for Data Manipulation

XLSX: To read and write excel files
Foreign: To read and write SAS,SPSS files
XML: To read and write XML File
JSON: To read and write Json files
Moments: To Find Skewness and Kurtosis
Httr: A set of useful tools for working with http connections
ggplot2: For visualixation purpose
lubridate: To work with date-spans, time-spans, date-time dd/mm/yy to yy/mm/dd
dplyr: Consistent and fast tool for working on R and modify the Data

Packages for Imputation

HotDeckimputation: To resolve missing Data

Yalmpute: Performs nearest neighbour-based imputation using one or more alternative approaches to process multivariate data

Mvnmle: Finds the maximum likelihood estimate of the mean vector and variance-covariance matrix for multivariate normal data with missing values.

Mice: Multiple Imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm

Lattice: A powerful, high-level data visualization system, emphasis on multivariate data. Sufficient for typical graphics needs, flexible to handle non-standard requirements.

Packages for Kmeans

Plyr: break a big problem down into pieces, operate on each piece and then put all the pieces back together.

Animation: Provides functions for animations in probability theory, mathematical, multivariate, nonparametric, computational statistics, sampling survey, linear models, time series, np data mining and machine learning.

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