## Road map…

- Why graphical representation of frequency distribution is needed?
- Barplot for frequency distribution
- Pie Charts for frequency distribution
- Histogram for frequency distribution
- Skewed Frequency Distribution
- Symmetrical Distribution of frequency

*Let’s start our journey…*

**What is Data Visualization?**

Data visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from. The main goal of data visualization is to find a pattern from data. Data visualization is one of the parts of Data Science. After collecting data we have to modify and modelling the data. At last, it should be visualized for final conclusions.

**Why graphical representation of frequency distribution is needed??**

To understand it deeply, you must have prior knowledge of Frequency Distribution. To know what is a frequency distribution, how to develop a frequency distribution table. You can read our previous article based on frequency distribution.

In our previous article, we may have a look at how to create a frequency distribution table from raw data. We may face another problem when we try to find patterns from the data. Do you guess how to analyze a frequency table to find patterns from a dataset? If you want to find a pattern from a frequency table, you have to look up the frequency of each unique value or class interval. Just by looking up the frequency of each unique value, can you find any pattern? No, you have to compare the frequencies of each value at the same time. It will be easy for a few unique values or class intervals, or when the frequency values are less and *easier to compare*. But we will get puzzled if we try to compare the frequency for a large number of unique values. We can solve this problem by visualizing the data. Graphs make it much easier to scan and compare frequencies, providing a single picture of the entire distribution of variables. Because they are easy to grasp and also eye-catching. Sometimes you have to represent data in front of a non-technical audience. Graphs are better way of representation if we need to present our findings to a non-technical audience. In this article, We’ll discuss three kinds of graphs to represent the distribution table:

*1.Bar Plots*

*2. Pie Charts*

*3. Histograms*

*We are considering a dataset for better demonstration*

Through this article, we are using the wnba.csv dataset. The **Women’s National Basketball Association** (**WNBA**)…

Continue reading: https://towardsdatascience.com/find-the-patterns-of-a-dataset-by-visualizing-frequency-distribution-c5718ab1f2c2?source=rss—-7f60cf5620c9—4

Source: towardsdatascience.com

## Comments by halbot