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103.3.2 Descriptive Statistics

As soon as we get some data, we can carry out descriptive statistics on it. Basic descriptive statistics gives an idea on the variable and their distribution, we get an overall picture of dataset and it also helps us to create a report on the data. There are 2 types …

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103.2.8 Exporting Data

Writing data in CSV file Another important feature available in R is the export function. With this function, the data created in R can be saved into any other format like the csv, xlsx, etc. Just as we used the function read.csv() to read the contents of the CSV file …

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103.2.7.a Merge and Join

In the telecom customer complaints data, most of the complaints are generally related to the Services or the Bills. The data on Bill and Complaints will gives us some relation between Bill payers and the Issues they are facing. “./Telecom Data Analysis/Bill.csv” “./Telecom Data Analysis/Complaints.csv” 1. Import the data and …

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103.2.7 Merge and Join

In R, we have merge() function to join the data sets into one. Syntax for merge function is: x <- merge(datasets1, dataset2, by="primary_key") The function above merges the dataset1 and dataset2, and saves the merged data into the variable x. We need to mention type of join otherwise the function …

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103.2.6 Handling Duplicates

Duplicates can be same or similar based on key (more than one) entries. Like, one customer purchasing multiple times in a single day from the same store. In R, we have a function called duplicated() which can be used to find repeated entries in the dataset.We get the index of …

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103.2.5 Sorting of Data

Sorting of the data can be considered as the fundamental part of the Data Analysis. User might want to sort the Names in the Alphabetical order, or wants to sort the Income data in the ascending order to find the highest tax payers, etc. Sorting is helpful in managing the …

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103.2.4 Calculated Fields in R

Calculated or the derived field is another important concept in data analysis. Sometimes not only the fields or the rows and columns of the raw data are sufficient for the data analysis, we might also have to do some operations and create some new fields. A new field can be …

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