eda-fb
In this blog, I want to perform Exploratory Data Analysis with Facebook dataset. This dataset contains almost 100,000 users and it varies from age, birthday,gender, to likes, mobile likes, etc..
Well this isn’t actually a real Facebook dataset. But this pseudo data is provided by Data Analysts at Facebook. So we can be assured it’s as good as the real one. This Exploratory Data Analysis ranging from my experience from Udacity Course, Exploratory Data Analysis with R, in which I acquired the dataset. You should check it, it’s really recommended course.
Here I generate the html using Knit HTML with Rstudio. the code is as given.
Overview
Now, to get better at analyzing at the dataset, it’s good to have all summary that we need to do this analysiz. First, I will do some basic summary to get better understand at the dataset. Here the dataset contain the words ‘dob’, which means data of birth.
## userid age dob_day dob_year
## Min. :1000008 Min. : 13.00 Min. : 1.00 Min. :1900
## 1st Qu.:1298806 1st Qu.: 20.00 1st Qu.: 7.00 1st Qu.:1963
## Median :1596148 Median : 28.00 Median :14.00 Median :1985
## Mean :1597045 Mean : 37.28 Mean :14.53 Mean :1976
## 3rd Qu.:1895744 3rd Qu.: 50.00 3rd Qu.:22.00 3rd Qu.:1993
## Max. :2193542 Max. :113.00 Max. :31.00 Max. :2000
##
## dob_month gender tenure friend_count
## Min. : 1.000 female:40254 Min. : 0.0 Min. : 0.0
## 1st Qu.: 3.000 male :58574 1st Qu.: 226.0 1st Qu.: 31.0
## Median : 6.000 NA's : 175 Median : 412.0 Median : 82.0
## Mean : 6.283 Mean : 537.9 Mean : 196.4
## 3rd Qu.: 9.000 3rd Qu.: 675.0 3rd Qu.: 206.0
## Max. :12.000 Max. :3139.0 Max. :4923.0
## NA's :2
## friendships_initiated likes likes_received
## Min. : 0.0 Min. : 0.0 Min. : 0.0
## 1st Qu.: 17.0 1st Qu.: 1.0 1st Qu.: 1.0
## Median : 46.0 Median : 11.0 Median : 8.0
## Mean : 107.5 Mean : 156.1 Mean : 142.7
## 3rd Qu.: 117.0 3rd Qu.: 81.0 3rd Qu.: 59.0
## Max. :4144.0 Max. :25111.0 Max. :261197.0
##
## mobile_likes mobile_likes_received www_likes
## Min. : 0.0 Min. : 0.00 Min. : 0.00
## 1st Qu.: 0.0 1st Qu.: 0.00 1st Qu.: 0.00
## Median : 4.0 Median : 4.00 Median : 0.00
## Mean : 106.1 Mean : 84.12 Mean : 49.96
## 3rd Qu.: 46.0 3rd Qu.: 33.00 3rd Qu.: 7.00
## Max. :25111.0 Max. :138561.00 Max. :14865.00
##
## www_likes_received
## Min. : 0.00
## 1st Qu.: 0.00
## Median : 2.00
## Mean : 58.57
## 3rd Qu.: 20.00
## Max. :129953.00
## ## userid age dob_day dob_year dob_month gender tenure friend_count
## 1 2094382 14 19 1999 11 male 266 0
## 2 1192601 14 2 1999 11 female 6 0
## 3 2083884 14 16 1999 11 male 13 0
## 4 1203168 14 25 1999 12 female 93 0
## 5 1733186 14 4 1999 12 male 82 0
## 6 1524765 14 1 1999 12 male 15 0
## friendships_initiated likes likes_received mobile_likes
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## mobile_likes_received www_likes www_likes_received
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0Lastly, we may want to plot each other variables against another so we can get a better insight.
Now let’s disscuss some of these graph.
Female vs Male
As this dataset also contain the gender, I want to know every analysis that differentiate the male from the female. First let’s take a look at each of the gender. Let’s see the friend count for both female and male.
## pf$gender: female
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0 37 96 242 244 4923
## --------------------------------------------------------
## pf$gender: male
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0 27 74 165 182 4917The median of female is better than male, because the mean in female will drag the median lefwards of the graph. The median will resistance about the outliers(friend_count hight), because the average we can say that we at least try half of our data.