Publications by Adnaan

WEEK-4(Updated)

15.11.2023

Cryptocurrency Price & Market Data Analysis The dataset includes information on various cryptocurrencies, detailing their names (coin), symbols, prices, percentage changes in the last hour (1h), 24 hours (24h), and 7 days (7d), 24-hour trading volume (24h_volume), market capitalization (mkt_cap) data=read.csv("C:/Users/Adnaan/Desktop/crypto.csv"...

2521 sym R (5874 sym/15 pcs) 9 img

WEEK-5

15.11.2023

World Happiness Report dataset analysis using plots.. data=read.csv("C:/Users/Adnaan/OneDrive/Documents/happiness.csv") print(data) ## Country Region HappinessRank ## 1 Switzerland Western Europe 1 ## 2 Iceland Western Europe ...

869 sym R (20471 sym/11 pcs) 3 img

WEEK-1

14.11.2023

R program to add two vectors of integers type and length 3. #vector sum x=c(1,2,3) y=c(4,6,8) k=x+y print(k) ## [1] 5 8 11 R program to find the Sum, Mean, and Product of a Vector. v=c(1,2,3,4) s=sum(v) print(s) ## [1] 10 m=mean(v) print(m) ## [1] 2.5 p=prod(v) print(p) ## [1] 24 R program to find the minimum and the maximum of a Vector. ...

844 sym

WEEK-3

14.11.2023

R plots… R Plots are visual representations of data that help analysts and data scientists explore, analyze, and communicate insights. R offers a rich ecosystem of plotting functions and libraries, each designed for specific data visualization needs. #One categorical and one continuous variable (Bar Chart) # Sample data data <- data.frame(Ca...

2063 sym 12 img

WEEK-2

14.11.2023

#Data manipulation in r… Data manipulation in R involves the systematic process of refining and restructuring data to enhance its quality and prepare it for analysis. This includes handling missing values, outliers, and transforming variables. Techniques like aggregation, subsetting, merging, and reshaping data are pivotal for extracting mea...

1224 sym R (39931 sym/64 pcs)

WEEK-2(updated)

14.11.2023

Data manipulation in r… Data manipulation in R involves the systematic process of refining and restructuring data to enhance its quality and prepare it for analysis. This includes handling missing values, outliers, and transforming variables. Techniques like aggregation, subsetting, merging, and reshaping data are pivotal for extracting meani...

1225 sym R (39931 sym/64 pcs)