[파이썬/proj] Screen Time Analysis

ScreenTimeAnalysis.html

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ScreenTimeAnalysis.ipynb

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Screentime-App-Details.csv

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Screen Time Analysis¶

Website: https://thecleverprogrammer.com/2022/10/24/screen-time-analysis-using-python/

Screen Time Analysis lets you know how much time you spend on what kind of applications and websites using your device. And screen time analysis gives a visual report of the same. So, if you want to learn how to analyze screen time, this article is for you. In this article, I will take you through the task of Screen Time Analysis using Python.

Screen Time Analysis¶

Screen Time Analysis is the task of analyzing and creating a report on which applications and websites are used by the user for how much time. Apple devices have one of the best ways of creating a screen time report.

For the task of screen time analysis, I found an ideal dataset that contains data about:

1. Date
2. Usage of Applications
3. Number of Notifications from Applications
4. Number of times apps opened

You can download the dataset from here: https://statso.io/screen-time-analysis-case-study/

https://statso.io/wp-content/uploads/2022/11/Screentime-App-Details.csv

In the section below, I will take you through the task of Screen Time Analysis using Python.

Screen Time Analysis using Python¶

Let’s start the task of screen time analysis by importing the necessary Python libraries and the dataset:

In [ ]:

import pandas as pd
import numpy as np
import plotly.express as px
import plotly.graph_objects as go

data = pd.read_csv("./Screentime-App-Details.csv")
print(data.head())

         Date  Usage  Notifications  Times opened        App
0  08/26/2022     38             70            49  Instagram
1  08/27/2022     39             43            48  Instagram
2  08/28/2022     64            231            55  Instagram
3  08/29/2022     14             35            23  Instagram
4  08/30/2022      3             19             5  Instagram

Now, let’s have a look at whether this dataset has any null values or not:

In [ ]:

data.isnull().sum()

Out[ ]:

Date             0
Usage            0
Notifications    0
Times opened     0
App              0
dtype: int64

The dataset doesn’t have any null values. Now let’s have a look at the descriptive statistics of the data:

In [ ]:

data.describe()

Out[ ]:

	Usage	Notifications	Times opened
count	54.000000	54.000000	54.000000
mean	65.037037	117.703704	61.481481
std	58.317272	97.017530	43.836635
min	1.000000	8.000000	2.000000
25%	17.500000	25.750000	23.500000
50%	58.500000	99.000000	62.500000
75%	90.500000	188.250000	90.000000
max	244.000000	405.000000	192.000000

Now let’s start with analyzing the screen time of the user. I will first look at the amount of usage of the apps:

In [ ]:

figure = px.bar(data_frame=data, x="Date", y="Usage", color="App", title="Usage")
figure.show()

Now let’s have a look at the number of notifications from the apps:

In [ ]:

figure = px.bar(data_frame=data, x="Date", y="Notifications", color="App", title="Notifications")
figure.show()

Now let’s have a look at the number of times the apps opened:

In [ ]:

figure = px.bar(data_frame=data, x="Date", y="Times opened", color="App", title="Times Opened")
figure.show()

We generally use our smartphones when we get notified by any app. So let’s have a look at the relationship between the number of notifications and the amount of usage:

In [ ]:

figure = px.scatter(data_frame=data,
                    x="Notifications", 
                    y="Usage", 
                    size="Notifications", 
                    trendline="ols", 
                    title="Relations Between Number of Notifications and Usage"
                    )
figure.show()

There’s a linear relationship between the number of notifications and the amount of usage. It means that more notifications result in more use of smartphones.

Summary¶

So this is how we can analyze the screen time of a user using the Python programming language. Screen Time Analysis is the task of analyzing and creating a report on which applications and websites are used by the user for how much time. I hope you liked this article on Screen Time Analysis using Python. Feel free to ask valuable questions in the comments section below.