-
Notifications
You must be signed in to change notification settings - Fork 0
/
Acquired Companies.Rmd
280 lines (219 loc) · 15.9 KB
/
Acquired Companies.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
---
title: "Acquired Companies"
author: "Anshuman Moudgil"
date: "16 June 2018"
output:
html_document:
number_sections: true
toc: true
fig_width: 7
fig_height: 4.5
theme: readable
highlight: tango
code_folding: hide
---
Version update (14 July 2018)
---------------------------------------------------------------
Kaggle URL: https://www.kaggle.com/anshumoudgil/acquired-companies-today-s-products/notebook
---------------------------------------------------------------
# Introduction
Companies Acquisitions Data - as of May 2018 - is quite interesting data. It furnished the list of companies who got acquired by one of the 7 companies like Apple, Facebook, Google, IBM, Microsoft, Twitter, and Yahoo!. Today we know those companies products by different names like Yahoo! 360°, Google's DeepMind, iTunes, iWorks, and Apple Maps etc.
Merger & Acquisitions is not a new phenomenon. Here it data depicted only technology sector but it is spread across all 23 industry sectors. This notebook, as a function of data provided, will try to emphasize on which were the companies that got acquired and how we know them today. Lets read it further.
## Libraries
```{r setup, include=FALSE}
library(ggplot2)
library(dplyr)
```
## Data
It is a small data of 10 variables and 916 observations. Here is the glimpse of data. A small point to note: there are many cells that are empty in Value (USD) column as they have not been mentioned.
```{r, warning=FALSE, message=FALSE}
acq <- read.csv("../input/acquisitions.csv", header = TRUE)
str(acq)
```
# First Look
The graph below is the 1st look of data. It shows how the old players like IBM, Apple, Microsoft, and Yahoo had remained regular acquirers. New players like Facebook, Twitter and Google too started had acquiring just like their old peers.
## Acquisitions - Year
The years from 2013 to 2015 remained most busy years for these 7 companies from acquisition point of view.
```{r, warning=FALSE}
acq %>% ggplot(aes(x = AcquisitionYear))+
geom_bar(aes(fill=ParentCompany))+
scale_fill_brewer(name="",palette='Paired')+
labs(title = "Companies Acquired vs. Year", x = "Year of Acquisition",y = "Number of companies acquired", subtitle = "7 Parent Companies")+
scale_x_reverse()+
theme_minimal()
```
## Acquisitions - Country of Origin
USA, Canada remained as biggest supplier of companies from technology point of view in Americas. In EU its United Kingdom, Germany, and France contributing the most. Israel - been promoted as start-up country - is placed at number 4 in overall hierarchy.
As per graph below (restricted to only those business categories where 3 or more acquisitions were made) many renowned products either have different country of origin or products of different countries contributed towards their present avatar.
```{r, warning=FALSE}
acq$sign <- "{"
TopicFreq <- acq %>% count(Business, sort = TRUE)
colnames(TopicFreq)[2] <- "Bfreq"
acq <- full_join(acq, TopicFreq, by = "Business")
rm(TopicFreq)
acq%>% filter(Bfreq > 2 & Derived.products != "")%>% ggplot(aes(y= Derived.products, x = Country))+
geom_jitter(size=5, color="blue", fill=alpha("white", 0.01), alpha=0.45, shape=21, stroke=1)+
theme(axis.text.y = element_text(size=6.85))+
theme_minimal()+
labs(title = "Country of Origin of Derived Products", x = "County of Origin",y = "Derived Product", subtitle = "Transformed to great products")
```
# Companies' lists
Each company has its own list of target companies. In following graphs I am trying to show only a small subset of complete data's list.
My criteria is most frequented Business Categories for acquisitions. If you (while analyzing) change the criteria then all these analysis will change or new thought would be required.
## Apple
```{r, warning=FALSE}
App <- acq %>% filter(Derived.products != "") %>% filter(Bfreq >3) %>% filter(ParentCompany =="Apple")
App <- App %>% arrange(AcquisitionYear)
App$id <- seq(1, nrow(App))
App$angle <- 90
ggplot(App, aes(x=as.factor(id), y=0.5))+
geom_point(size=1, color="white", fill=alpha("white", 0.0001), alpha=0.01, shape=8, stroke=1)+
ylim(-20,20)+theme_minimal() +
theme(
axis.text = element_blank(),
panel.grid = element_blank())+
geom_text(data=App, aes(x=id, y= 5, label=Derived.products, hjust=0, vjust = 0.5), color="grey27", fontface="bold",alpha=0.72, size=3.75, angle= App$angle, inherit.aes = FALSE)+
geom_text(data=App, aes(x=id, y= -1.5, label=sign, hjust=0, vjust=0.5), color="grey27", alpha=0.72, size=9, angle=270, inherit.aes = FALSE)+
geom_text(data=App, aes(x=id, y= 0.5, label=AcquisitionYear, hjust=0.5, vjust=0.5), color="grey27", alpha=0.81, size=3.25, angle=0, inherit.aes = FALSE)+
geom_text(data=App, aes(x=id, y= 3, label=Country, hjust=0.5, vjust=0.5), color="grey27", alpha=0.81, size=3.25, angle=0, inherit.aes = FALSE)+
geom_text(data=App, aes(x=id-0.175, y= -5, label=Company, hjust = 0), color="maroon4", fontface="bold",alpha=0.87, size=3.25, angle= App$angle+180, inherit.aes = FALSE)+
geom_text(data=App, aes(x=id+0.175, y= -5, label=Business, hjust = 0), color="blue4", fontface="bold",alpha=0.9, size=3.25, angle= App$angle+180, inherit.aes = FALSE)+
labs(title = "Apple", x="Acquired company's name & original Business",y="Transformed to Product", subtitle = "Apple's present day products, preceded by Year & Country of Origin")
```
## Facebook
```{r, warning=FALSE}
FB <- acq %>% filter(Bfreq >1) %>% filter(ParentCompany =="Facebook")
FB <- FB %>% arrange(AcquisitionYear)
FB$id <- seq(1, nrow(FB))
FB$angle <- 90
ggplot(FB, aes(x=as.factor(id), y=0.5))+
geom_point(size=1, color="white", fill=alpha("white", 0.0001), alpha=0.01, shape=8, stroke=1)+
ylim(-20,20)+theme_minimal() +
theme(
axis.text = element_blank(),
panel.grid = element_blank())+
geom_text(data=FB, aes(x=id, y= 5, label="...Facebook", hjust=0, vjust = 0.5), color="blue4", fontface="bold",alpha=0.72, size=3.75, angle= FB$angle, inherit.aes = FALSE)+
geom_text(data=FB, aes(x=id, y= -1.5, label=sign, hjust=0, vjust=0.5), color="blue4", alpha=0.72, size=9, angle=270, inherit.aes = FALSE)+
geom_text(data=FB, aes(x=id, y= 0.5, label=AcquisitionYear, hjust=0.5, vjust=0.5), color="blue4", alpha=0.81, size=3.25, angle=0, inherit.aes = FALSE)+
geom_text(data=FB, aes(x=id, y= 3, label=Country, hjust=0.5, vjust=0.5), color="blue4", alpha=0.81, size=3.25, angle=0, inherit.aes = FALSE)+
geom_text(data=FB, aes(x=id-0.175, y= -5, label=Company, hjust = 0), color="red", fontface="bold",alpha=0.87, size=3.25, angle= FB$angle+180, inherit.aes = FALSE)+
geom_text(data=FB, aes(x=id+0.175, y= -5, label=Business, hjust = 0), color="green4", fontface="bold",alpha=0.9, size=3.25, angle= FB$angle+180, inherit.aes = FALSE)+
labs(title = "Facebook", x="Acquired company's name & original Business",y="Transformed to Product", subtitle = "Facebook's present day products, preceded by Year & Country of Origin")
```
## Google
```{r, warning=FALSE}
Goo <- acq %>% filter(Derived.products != "") %>% filter(Bfreq >3) %>% filter(ParentCompany =="Google")
Goo <- Goo %>% arrange(AcquisitionYear)
Goo$id <- seq(1, nrow(Goo))
Goo$angle <- 90
ggplot(Goo, aes(x=as.factor(id), y=6))+
geom_point(size=3, color="red", fill=alpha("lemonchiffon", 0.63), alpha=0.81, shape=21, stroke=1)+
ylim(-20,20)+theme_minimal()+
theme(
axis.text = element_blank(),
panel.grid = element_blank())+
geom_text(data=Goo, aes(x=id, y= 8, label=Derived.products, hjust=0), color="black", alpha=0.72, size=3, angle= Goo$angle, inherit.aes = FALSE)+
geom_text(data=Goo, aes(x=id, y= 1.5, label=AcquisitionYear, hjust=0.5, vjust=0.5), color="black", alpha=0.81, size=2.5, angle=Goo$angle, inherit.aes = FALSE)+
geom_text(data=Goo, aes(x=id, y= -4, label=Country, hjust=0.5, vjust=0.5), color="black", alpha=0.81, size=2.5, angle=0, inherit.aes = FALSE)+
geom_text(data=Goo, aes(x=id-0.175, y= -6, label=Company, hjust = 0), color="maroon4", fontface="bold",alpha=0.87, size=2.5, angle= Goo$angle+180, inherit.aes = FALSE)+
geom_text(data=Goo, aes(x=id+0.175, y= -6, label=Business, hjust = 0), color="blue4", fontface="bold",alpha=0.9, size=2.5, angle= Goo$angle+180, inherit.aes = FALSE)+
labs(title = "Google", x="Acquired company's name & original Business",y="Transformed to Product", subtitle = "Google's present day products, preceded by Country of Origin & Year")
```
## IBM
```{r, warning=FALSE}
IBM <- acq %>% filter(Bfreq >2) %>% filter(ParentCompany =="IBM")
IBM <- IBM %>% arrange(AcquisitionYear)
IBM$id <- seq(1, nrow(IBM))
IBM$angle <- 90
ggplot(IBM, aes(x=as.factor(id), y=0.5))+
geom_point(size=3, color="cornflowerblue", fill=alpha("cornflowerblue", 0.0001), alpha=0.95, shape=8, stroke=1)+
ylim(-20,20)+theme_minimal() +
theme(
axis.text = element_blank(),
panel.grid = element_blank())+
geom_text(data=IBM, aes(x=12, y= 16.5, label="IBM's Products", hjust=0), color="cornflowerblue",alpha=0.95, size=6, angle= IBM$angle-90, inherit.aes = FALSE)+
geom_text(data=IBM, aes(x=id, y= 10, label=AcquisitionYear, hjust=0.5, vjust=0.5), color="cornflowerblue", alpha=0.95, size=3.25, angle=IBM$angle, inherit.aes = FALSE)+
geom_text(data=IBM, aes(x=id, y= 4.5, label=Country, hjust=0.5, vjust=0.5), color="cornflowerblue", alpha=0.95, size=2.5, angle=0, inherit.aes = FALSE)+
geom_text(data=IBM, aes(x=id-0.175, y= -3, label=Company, hjust = 0), color="maroon4", fontface="bold",alpha=0.87, size=2.5, angle= IBM$angle+180, inherit.aes = FALSE)+
geom_text(data=IBM, aes(x=id+0.175, y= -3, label=Business, hjust = 0), color="blue4", fontface="bold",alpha=0.9, size=2.5, angle= IBM$angle+180, inherit.aes = FALSE)+
labs(title = "IBM", x="Acquired company's name & original Business",y="Transformed to Product", subtitle = "IBM's present day products, preceded by Country of Origin & Year")
```
## Microsoft - I
```{r, warning=FALSE}
MS <- acq %>% filter(Bfreq >2) %>% filter(ParentCompany =="Microsoft") %>% filter(Business !="Software")
MS <- MS %>% arrange(AcquisitionYear)
MS$id <- seq(1, nrow(MS))
MS$angle <- 90
ggplot(MS, aes(x=as.factor(id), y=0))+
geom_point(size=3, color="slateblue4", fill=alpha("slateblue4", 0.63), alpha=1, shape=3, stroke=1)+
ylim(-20,20)+theme_minimal()+
theme(
axis.text = element_blank(),
panel.grid = element_blank())+
geom_text(data=MS, aes(x=8, y= 18, label="Microsoft's Inventory", hjust=0), color="slateblue4",alpha=0.72, size=5, angle= MS$angle-90, inherit.aes = FALSE)+
geom_text(data=MS, aes(x=id, y= 10, label=AcquisitionYear, hjust=0.5, vjust=0.5), color="black", alpha=0.72, size=3.25, angle=MS$angle, inherit.aes = FALSE)+
geom_text(data=MS, aes(x=id, y= 4.5, label=Country, hjust=0.5, vjust=0.5), color="black", alpha=0.72, size=2.75, angle=0, inherit.aes = FALSE)+
geom_text(data=MS, aes(x=id-0.175, y= -4, label=Company, hjust = 0), color="maroon", fontface="bold",alpha=0.87, size=2.75, angle= MS$angle+180, inherit.aes = FALSE)+
geom_text(data=MS, aes(x=id+0.175, y= -4, label=Business, hjust = 0), color="navyblue", fontface="bold",alpha=0.9, size=2.75, angle= MS$angle+180, inherit.aes = FALSE)+
labs(title = "Microsoft", x="Acquired company's name & original Business",y="Transformed to Product", subtitle = "Microsoft acquired maximum businesses in Software category - the graph here is most but Software")
```
## Microsoft - II
```{r, warning=FALSE}
MS2 <- acq %>% filter(ParentCompany =="Microsoft") %>% filter(Value..USD. >125000000)
MS2 <- MS2 %>% arrange(AcquisitionYear)
MS2$id <- seq(1, nrow(MS2))
MS2$angle <- 90
ggplot(MS2, aes(x=as.factor(id), y=0))+
geom_point(size=3, color="slateblue", fill=alpha("slateblue", 0.63), alpha=0.81, shape=5, stroke=1)+
ylim(-20,20)+theme_minimal()+
theme(
axis.text = element_blank(),
panel.grid = element_blank())+
geom_text(data=MS2, aes(x=id, y= 6, label=Company, hjust=0), color="black",alpha=0.72, fontface="bold",size=3.5, angle= MS2$angle, inherit.aes = FALSE)+
geom_text(data=MS2, aes(x=id, y= 3.75, label=AcquisitionYear, hjust=0.5, vjust=0.5), color="black", alpha=0.81, size=2.5, angle=0, inherit.aes = FALSE)+
geom_text(data=MS2, aes(x=id, y= -3.75, label=Country, hjust=0.5, vjust=0.5), color="black", alpha=0.81, size=2.5, angle=0, inherit.aes = FALSE)+
geom_text(data=MS2, aes(x=id, y= -6.5, label=Business, hjust = 0), color="blue4", fontface="bold",alpha=0.9, size=3, angle= MS2$angle+180, inherit.aes = FALSE)+
labs(title = "Microsoft's Billion Dollar Assests", x="Acquired company's original Business & Country",y="", subtitle = "Microsoft acquired them - in YEAR - and paid anything from x10^8 to x10^10")
```
## Twitter
```{r, warning=FALSE}
Twt <- acq %>% filter(ParentCompany =="Twitter") %>% filter(Derived.products!="")
Twt <- Twt %>% arrange(Business)
Twt$id <- seq(1, nrow(Twt))
Twt$angle <- 90
ggplot(Twt, aes(x=as.factor(id), y=0))+
geom_rug()+theme_minimal() +
theme(
axis.text = element_blank(),
panel.grid = element_blank())+
geom_text(data=Twt, aes(x=id, y= -0.3, label=Derived.products, hjust=0), color="royalblue", fontface="bold",alpha=0.92, size=3.5, angle= Twt$angle, inherit.aes = FALSE)+
geom_text(data=Twt, aes(x=id, y= -0.37, label=Country, hjust=0.5, vjust=0.5), color="royalblue", alpha=0.99, size=2.75, angle=0, inherit.aes = FALSE)+
geom_text(data=Twt, aes(x=id, y= -0.4, label=AcquisitionYear, hjust=0.5, vjust=0.5), color="royalblue", alpha=0.99, size=2.75, angle=0, inherit.aes = FALSE)+
geom_text(data=Twt, aes(x=id-0.175, y= -0.325, label=Company, hjust = 0), color="maroon", fontface="bold",alpha=0.87, size=2.75, angle= Twt$angle, inherit.aes = FALSE)+
geom_text(data=Twt, aes(x=id+0.175, y= -0.325, label=Business, hjust = 0), color="navyblue", fontface="bold",alpha=0.9, size=2.75, angle= Twt$angle, inherit.aes = FALSE)+
labs(title = "Twitter", x="Acquired company's name (in maroon) & original Business (in blue)",y="Transformed to...", subtitle = "Twitter's present day products, preceded by Year & Country of Origin")
```
## Yahoo!
```{r, warning=FALSE}
Yah <- acq %>% filter(Bfreq >2) %>% filter(ParentCompany =="Yahoo")
Yah <- Yah %>% arrange(AcquisitionYear)
Yah$id <- seq(1, nrow(Yah))
Yah$angle <- 90
ggplot(Yah, aes(x=as.factor(id), y=0.5))+
geom_point(size=1, color="white", fill=alpha("white", 0.0001), alpha=0.01, shape=8, stroke=1)+
ylim(-20,20)+theme_minimal() +
theme(
axis.text = element_blank(),
panel.grid = element_blank())+
geom_text(data=Yah, aes(x=id, y= 5, label=Derived.products, hjust=0, vjust = 0.5), color="darkorchid4", fontface="bold",alpha=0.81, size=3.75, angle= Yah$angle, inherit.aes = FALSE)+
geom_text(data=Yah, aes(x=id, y= -1.5, label=sign, hjust=0, vjust=0.5), color="darkorchid4", alpha=0.81, size=9, angle=270, inherit.aes = FALSE)+
geom_text(data=Yah, aes(x=id, y= 0.5, label=AcquisitionYear, hjust=0.5, vjust=0.5), color="darkorchid4", alpha=0.81, size=3.25, angle=0, inherit.aes = FALSE)+
geom_text(data=Yah, aes(x=id, y= 3, label=Country, hjust=0.5, vjust=0.5), color="darkorchid4", alpha=0.81, size=3.25, angle=0, inherit.aes = FALSE)+
geom_text(data=Yah, aes(x=id-0.175, y= -5, label=Company, hjust = 0), color="maroon", fontface="bold",alpha=0.87, size=3.25, angle= Yah$angle+180, inherit.aes = FALSE)+
geom_text(data=Yah, aes(x=id+0.175, y= -5, label=Business, hjust = 0), color="navyblue", fontface="bold",alpha=0.9, size=3.25, angle= Yah$angle+180, inherit.aes = FALSE)+
labs(title = "Yahoo!", x="Acquired company's name & original Business",y="Transformed to Product", subtitle = "Yahoo's today's products, preceded by Year & Country of Origin")
```
# Conclusion
Acquisition of companies (big, small, or start-ups) is one of the ways for a given company to grow. The objective behind acquisition can be anything like revenue growth, market access, technological know-how, or talent etc. It's not limited to one sector or a geography. In this notebook only 7 technology companies had been mentioned, but there are many more. Hope by reading these graphs you may easily recall in future which company was acquired by whom and by what name we know them today.
Hope you enjoyed reading and data presentation. Please do up-vote and or write a comment to share your opinions.
Thanks