Let’s Create a Bar Graph in Python using CSV data.
A bar graph is a chart that plots data using rectangular bars or columns (called bins) that represent the total amount of observations in the data for that category. Bar charts can be displayed with vertical columns, horizontal bars, comparative bars (multiple bars to show a comparison between values), or stacked bars (bars containing multiple types of information).
What Is a CSV File?
A CSV File (comma-separated values) is a text file that stores data in the form of columns, separated by commas, and rows are distinguished by line breaks.
Comma separated value file means that the data is actually input as data that is separated by commas. The spreadsheet application converts those comma-separated pieces of data into cells in tables and columns to make it easier to read and edit.
Now let’s start creating bar graph.
- First we have to Import necessary modules
2. Next we have to read the csv file data.
here we are using a csv file named ‘data.csv’.
3. Create DataFrame
4. Initialize the lists for X and Y
.iloc[] is primarily integer position based (from 0 to length-1 of the axis), but may also be used with a boolean array.
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Plot CSV Data in Python
Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.
CSV or comma-delimited-values is a very popular format for storing structured data. In this tutorial, we will see how to plot beautiful graphs using csv data, and Pandas. We will learn how to import csv data from an external source (a url), and plot it using Plotly and pandas.
First we import the data and look at it.
| AAPL_x | AAPL_y | |
|---|---|---|
| 0 | 2014-01-02 | 77.445395 |
| 1 | 2014-01-03 | 77.045575 |
| 2 | 2014-01-06 | 74.896972 |
| 3 | 2014-01-07 | 75.856461 |
| 4 | 2014-01-08 | 75.091947 |
Plot from CSV with Plotly Express¶
Plot from CSV in Dash¶
Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash , click «Download» to get the code and run python app.py .
Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.
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Plot from CSV with graph_objects ¶
Reference¶
See https://plotly.com/python/getting-started for more information about Plotly’s Python API!
What About Dash?¶
Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.
Python Plot CSV
CSV stands for Comma Separated Values, a popular format to store structured data. The CSV file contains the data in the form of a table with rows and columns.
We often need to visualize the data stored in the CSV file. For this purpose, Python provides different kinds of plots for data visualization.
Use matplotlib.pyplot to Visualize the CSV Data in Python
Matplotlib is an open-source and popular data visualization library in Python. It has a sub-module called pyplot , used to plot graphs in Python.
To use matplotlib , we must install it first using the following command.
Use Bar Plot to Visualize CSV Data
A bar plot is a graph that contains rectangular bars that display the numeric values for categorical feature levels as bars. We will use the bar() method of the pyplot module to plot a bar graph.
In the following code, we have read the data from the CSV file using the read_csv() method available in the pandas module. The names and grades were retrieved from the data and transformed into lists.
The x represents the independent variable students’ names on the x-axis. The list y represents the students’ marks, which will appear on the y-axis.
We used the bar() method and passed the arguments. The width of the bar is 0.5, and the legend is Marks .
Finally, we have invoked the show() method, which will display the bar graph in the output.