Explore topic-wise InterviewSolutions in Current Affairs.

HDFS can be used for STORING the data for long-term. MapReduce jobs submitted from either Oozie, Pig or Hive can be used to encode, improve and sample the data sets from HDFS into R. This helps to leverage COMPLEX ANALYSIS tasks on the subset of data prepared in R.

HDFS can be used for storing the data for long-term. MapReduce jobs submitted from either Oozie, Pig or Hive can be used to encode, improve and sample the data sets from HDFS into R. This helps to leverage complex analysis tasks on the subset of data prepared in R.

SAVE (X, FILE=”x.Rdata”)

save (x, file=”x.Rdata”)

• BUCKET Sort
• SELECTION Sort
• QUICK Sort
• Bubble Sort
• MERGE Sort

BOXPLOT () or TEXT ()

boxplot () or text ()

data.table

data.table

With () FUNCTION is USED to apply an expression for a given dataset and BY () function is used for APPLYING a function each level of factors.

With () function is used to apply an expression for a given dataset and BY () function is used for applying a function each level of factors.

TRANSPOSE t () is the easiest method for RESHAPING the data before ANALYSIS.

Transpose t () is the easiest method for reshaping the data before analysis.

MYTABLE= data.frame ()

edit (MyTable)

The above CODE will OPEN an Excel Spreadsheet for entering data into MyTable.

Learn Data SCIENCE in R Programming to land a top gig as an Enterprise Data SCIENTIST!

MyTable= data.frame ()

edit (MyTable)

The above code will open an Excel Spreadsheet for entering data into MyTable.

Learn Data Science in R Programming to land a top gig as an Enterprise Data Scientist!

R language has Homogeneous and Heterogeneous DATA structures.

Homogeneous data structures have same type of objects – VECTOR, Matrix ad Array.

Heterogeneous data structures have DIFFERENT type of objects – Data frames and LISTS.

R language has Homogeneous and Heterogeneous data structures.

Homogeneous data structures have same type of objects – Vector, Matrix ad Array.

Heterogeneous data structures have different type of objects – Data frames and lists.

The best possible way to do this is combine the data, code and analysis results in a single document using knitr for REPRODUCIBLE research. This helps others to verify the findings, add to them and engage in DISCUSSIONS. Reproducible research MAKES it easy to redo the experiments by INSERTING new data and applying it to a different problem.

The best possible way to do this is combine the data, code and analysis results in a single document using knitr for reproducible research. This helps others to verify the findings, add to them and engage in discussions. Reproducible research makes it easy to redo the experiments by inserting new data and applying it to a different problem.

t.tests ()

t.tests ()

CRAN package ECOSYSTEM has more than 6000 packages. The best way for beginners to answer this question is to mention that they WOULD look for a package that FOLLOWS good software development principles. The next THING would be to look for user reviews and FIND out if other data scientists or analysts have been able to solve a similar problem.

CRAN package ecosystem has more than 6000 packages. The best way for beginners to answer this question is to mention that they would look for a package that follows good software development principles. The next thing would be to look for user reviews and find out if other data scientists or analysts have been able to solve a similar problem.

NaN (Not a Number) is used to represent impossible VALUES whereas NA (Not Available) is used to represent missing values. The best WAY to answer this question would be to mention that deleting missing values is not a good IDEA because the probable cause for missing value could be some problem with data collection or programming or the query. It is good to FIND the root cause of the missing values and then take NECESSARY steps handle them.

NaN (Not a Number) is used to represent impossible values whereas NA (Not Available) is used to represent missing values. The best way to answer this question would be to mention that deleting missing values is not a good idea because the probable cause for missing value could be some problem with data collection or programming or the query. It is good to find the root cause of the missing values and then take necessary steps handle them.

R Commander is used to import data in R language. To start the R commander GUI, the user must type in the command Rcmdr into the CONSOLE. There are 3 DIFFERENT ways in which data can be imported in R language-

• Users can select the data set in the dialog box or enter the name of the data set (if they know).
• Data can also be entered directly using the EDITOR of R Commander VIA Data->New Data Set. However, this works well when the data set is not too large.
• Data can also be imported from a URL or from a plain text file (ASCII), from any other statistical package or from the clipboard.

R Commander is used to import data in R language. To start the R commander GUI, the user must type in the command Rcmdr into the console. There are 3 different ways in which data can be imported in R language-