Time-Series graphs

What are the graphs & why data visualization is essential?

A graph is a diagrammatic representation of the relationship between one or many variables, compounds all the information from data set in ths form of visualization. It allows trends and patterns to be more easily seen. I find graphs a fascinating way of communication with data.

Time Series Graphs –

While browsing through R graph gallery, I was amazed to find some exciting and unique data visualizations in the form of graphs, after much thought, I chose time series as it seemed something that interests me. Time-series graphs represent one or many variables through time; it can help to comprehend a great story about the data and makes visualization interesting. Time-series graphs can be easily plotted in R using package ggplot2: Create Elegant Data Visualizations Using the Grammar of Graphics and xts: eXtensible Time Series.

Why I chose the Time-series graph & what it does well?

The foremost reason for choosing Time-series graphs is that it seems very familiar because of the vast usage of the graph in day to day life. Time-series graphs play a vital role in many real-life scenarios plotting trends over time, tracking temperature data, economic indicators over time, monitoring election results, forecasting, and lot more. Secondarily, it is straightforward to conclude from time-series graphs because these are highly interpretable. Also easy to create as well in any programming language. It is considered on the best graphs and can help to immensely improve the efficiency of presentation.

Any graph which represents variation in one or many variables over time comes under time-series graph line graphs, stacked area chart, bar charts, and grant charts all are considered time-series graphs.

My favorite example of Time-series graph is “Visualizing seven years of Twitter evolution 2012:2018,” a Forbes article that shows several twitter users per quarter. It shows the variation of verified tweets and verified users over time, estimated total daily tweets from 1% of stream, average tweet per user from the Twitter 1% stream over the team.

How can we make the Time-series graph better?

• The graph will become more interactive and exciting with the addition of three dimensional or animated components; it will look more promising too.
• As time-series graphs get used in plotting trends, incorporation of the trend line for future predictions will make this graph more functional in real-time.
• As we use Time-series graphs vividly for forecasting, fluctuations related to several factors overtime should be considered under some parameters.