Xts Cheat Sheet

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Big Data¶

Parallel Computing¶

  • parallel. PDF.

sparklyr¶

  1. Cheat Sheet for R Data Visualizations. May 21, 2019; 8. It can automatically graph data from an xts object. You can also add overlays like shaded.
  2. The XSS cheat sheet provides you a list of snippets to be used in detecting XSS vulnerabilities.

본 문서는 지속적으로 업데이트됩니다.Basic123456789 link.

  • sparklyr. PDF.


Data mining and modeling¶

  • Data Mining. PDF only.
    • association rules, sequential patterns, classification & prediction, regression, clustering, outliers, time series, text mining, socila networks, graph mining, spatial data, statistics, graphics, data manipulation, data access, big data, parallel computing, reports, weka, editors, guis

data.table¶

  • data.table Intro. PDF only (explanatory article).
  • data.table. PDF.


dplyr¶

  • Grammar of dplyr. PDF only (explanatory slides).
  • dplyr. PDF.


forcats¶

  • forcats. PDF.

sjmisc¶

  • sjmisc. PDF.

Import and Tidy up¶

  • readr and tidyr. PDF.


Machine Learning¶

caret¶

  • caret. PDF.


estimatr¶

  • estimatr. PDF.

h2o¶

  • h2o. PDF.


Keras¶

  • Keras. PDF.


Machine Learning¶

  • Machine Learning. PDF only.

    • Supervised Learning;
    • Unsupervised Learning;
    • Deep Learning;
    • Machine Learning Tips and Tricks;
    • Probabilities and Statistics;
    • Linear Algebra and Calculus.

  • Big Data Machine Learning. PDF only.

    • linear regression, logistic regression, regularization (ridge, lasso), neural network, support vector machine, nayesian network and naïve bayes, k-nearest neighbors, decision tree, tree ensembles (bagging or random forest, boosting)

  • Machine Learning Modelling in R. PDF.


mlr¶

  • mlr. PDF.


Regressions¶

  • Regressions. PDF only.
    • linear model, variable selection, diagnostics, graphics, tests, variable transformation, ridge, segmented, gls, glm, nls, gnls, loess, splines, robust, structural equation, simultaneous equation, pls, principal components, quantile, linear and nonlinear mixed effects, generalized additive, survival analysis, classification & regression trees, beta

Survival Analysis¶

  • survminer. PDF only.
    • curve, ggplot2, cox model

NLP¶

quanteda¶

  • quanteda. PDF.


Regex¶

  • Basic Regular Expressions. PDF.

stringr¶

  • stringr. PDF.


xplain¶

  • xplain. PDF.

Probabilities and randomness¶

Probabilities¶

  • Probability Cheat Sheet. PDF only.

  • Probabilities. PDF.



randomizr¶

  • randomizr. PDF.

vtree¶

  • vtree. PDF.

Programming¶

purrr¶

  • purrr. PDF.


rlang¶

  • rlang. PDF.

Museum violin da salo.

Python¶

reticulate¶

  • reticulate. PDF.

Cheat


Quandl¶

Xts Cheat Sheet 2020

  • Quandl. PDF.


Time Series¶

lubridate¶

  • lubridate. PDF.


nardl¶

  • nardl. PDF.

Time series¶

  • Time Series. PDF only.
    • input, decomposition, tests, stochastic, graphics, miscellaneous

tsbox¶

  • tsbox. PDF.

xts¶

  • xts. PDF.

Tidyverse¶

  • Tidyverse. PDF.

Syntax¶

  • Syntax. PDF.


Even though the data.frame object is one of the core objects to hold data in R, you’ll find that it’s not really efficient when you’re working with time series data. You’ll find yourself wanting a more flexible time series class in R that offers a variety of methods to manipulate your data.

xts or the Extensible Time Series is one of such packages that offers such a time series object. It’s a powerful R package that provides an extensible time series class, enabling uniform handling of many R time series classes by extending zoo, which is the package that is the creator for an S3 class of indexed totally ordered observations which includes irregular time series.

xts has a lot to offer to make your time series analysis fast and mistake free, but it can take some time to get used to it.

This xts cheat sheet provides you not only with an overview of the xts object, how to create and inspect them, but also goes deeper into how you can manipulate time series with xts: you’ll see how to replace and update values, how to select, index and subset your objects, how to handle missing values and how to perform arithmetic operations.

Click on the button below to see (and download) the xts cheat sheet:

(Click above to download a printable version or read the online version below.)

This cheat sheet will help you to get yourself up to speed in no time!

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R For Data Science Cheat Sheet: xts

eXtensible Time Series (xts) is a powerful package that provides an extensible time series class, enabling uniform handling of many R time series classes by extending zoo.

Load the package as follows:

Xts Objects

xts objects have three main components:

  • coredata: always a matrix for xts objects
  • index: vector of any Date, POSIXct, chron, yearmon, yearqtr, or DateTime classes
  • xtsAttributes: arbitrary attributes

Creating xts Objects

Convert To And From xts

Import From Files

Inspect Your Data

Extract core data of objects

Extract index from objects

Class Attributes

Get index class

Cheat

Replacing index class

Get index class

Change format of time display

Time Zones

Change the time zone

Extract the current time zone

Periods, Periodicity & Timestamps

Sims 4 cc realistic. Estimate frequency of observations

Convert xts5 to yearly OHLC

Convert xts3 to monthly OHLC

Convert xts5 to quarterly OHLC

Convert to quarterly OHLC

Convert to yearly OHLC

Count the months in xts5

Count the quarters in xts5

Count the years in xts5

Make index unique

Remove duplicate times

Round index time to the next n seconds

Other Useful Functions

Extract raw numeric index of xts1

value of weekday in index of xts3

Value of hour in index of xts3

Extract first observation of xts3

Extract last observation of xts4

Display structure of xts3

Extract raw numeric index of xts1

First part of xts2

Last part of xts2

Export xts Objects

Replace & Update

Replace values in xts2 on dates with 0

Replace dates from 1961 with NA

Replace the value at 1 specific index with NA

Applying Functions

Locate endpoints by time

Calculate the yearly mean

Split xts5 by year

Create a list of yearly means

Find the last observation in each year in xts5

Calculate cumulative annual passengers

Apply standard deviation to rolling margins of xts5

Selecting, Subsetting & Indexing

Select

Subset

Get all data from 1954

Extract data from Jan to March ‘54

Get all data until March ‘54

Dr web serial. Subset xts4 using ep2

first() and last()

Indexing

Extract rows with the index of xts3

Extract rows using the vector days

Extract rows using days as POSIXct

Index of weekend days

Extract weekend days of xts1

Missing Values

Omit NA values in xts5

Fill missing values in xts2 using last observation

Fill missing values in xts2 using next observation

Interpolate NAs

Arithmetic Operations

coredata() or as.numeric()

Xts Cheat Sheet R

Shifting Index Values

Period-over-period differences

Lagged differences

Reindexing

Merging

Going Further

Xts Cheat Sheet Printable

Want to know more about xts? Check out DataCamp’s Manipulating Time Series Data in R with xts & zoo course!