Little Book
1 Introduction
2 Variable Types
- 2.1 Numeric Variables
- 2.2 Categorical Variables
3 Graph Types
4 Grammar of Data manipulation
- 4.1 Reorder function
I Womens Tennis
5 Introduction
6 Load Libraries
7 Read the data
8 Countries and Players
9 Rankings and Year
10 Number of No 1 Tennis Players each year
- 10.1 Number of No 1 Tennis Players from 2017 to 2003
- 10.2 Number of No 1 Tennis Players from 1984 to 2003
11 Trend of rankings of Serena Williams
- 11.1 Rankings above 100
12 Trend of rankings of Steffi Graf
13 Trend of rankings of Simona Halep
14 Trend of rankings of Sania Mirza
15 Australian Open Winners
- 15.1 Distribution of Age of Australian Open Winners
16 French Open Winners
- 16.1 Distribution of Age of French Open Winners
17 Wimbledon Winners
- 17.1 Distribution of Age of Wimbledon Winners
18 US Open Winners
- 18.1 Distribution of Age of US Open Winners
19 Height difference between winners and losers
20 Age difference between winners and losers
21 Feature Engineering : First, Second , Third Set Winners and Losers
22 Surfaces
23 Tournament Levels
24 Upsets
25 Simona Halep
26 Caroline Wozniacki
27 Height of players across years
- 27.1 Tabular Data of Heights across years
II Meteorite Landings
28 Prepare for Analysis
29 Read the Data
- 29.1 Peek into the Data
30 Class Analysis
- 30.1 Meteorites Class Count
  - 30.1.1 Top 20 Class Of Meteorites by Count
  - 30.1.2 Top 20 Meteorites and their Counts
- 30.2 Top 20 Class Of Meteorites by Mass
31 Distribution of Mass
32 Distribution of Meteorite Landings
- 32.1 Distribution of Meteorite Landings with Meteorite Mass
33 Distribution of Indian Meteorite Landings
34 Distribution of US Meteorite Landings
35 Distribution of African Meteorite Landings with Meteorite Mass
36 Distribution of Aus Meteorite Landings with Meteorite Mass
37 Year Analysis
38 L6 Meteorite Analysis
III Adverse Food Event
39 Read the Data
40 Peek into the Data
41 Rename Fields
42 Ten Most Common Symptoms
43 Ten Most Common Product Name
44 Ten Most Common Industry Name
45 Ages Commonly Affected
46 Distribution of Ages
47 Ten Most Common Outcomes
48 Outcomes and Products associated with Adverse Events
49 Symptoms and the Products Causing it
50 Time Analysis of Adverse Events
- 50.1 Year wise
- 50.2 Most Common Month for Adverse Events
51 Products in Adverse Events for January
52 Gender and Adverse Events
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Little Book on Exploratory Data Analysis

Chapter 6 Load Libraries

library(tidyverse)
library(stringr)
library(lubridate)
library(knitr)
library(kableExtra)
library(DT)