Introduction – Data Visualization is necessary and indeed a very interesting scope of work while solving any Data Science problem. There are several licensed and open-source Data Visualization tools available in the market like Tableau, Power BI, DataWrapper, Infogram, etc. Having said that, Python is in no way behind and provides some amazing libraries to perform Data Visualization activities. In relation to Python Programming Language, we have established some fundamental concepts in our previous few tutorials like Python Data Types, Loops in Python. There are various ways to visualize data by creating Histogram, Bar Plot, Scatter Plot, Box Plot, Heat Map, Line Chart, etc. In this article, we are going to look at how to create a scatter plot in Python using the widely used libraries like Pandas, Seaborn, Matplotlib, etc. The data set we are going to use for our charts is the Diamond data from the Kaggle website. Let us import the diamonds.csv and create a data frame out of it in Python using Pandas. We can see the first few rows of the data frame as well using the head command. import pandas as pd import seaborn as sns !pip install matplotlib import matplotlib.pyplot as plt from pandas import ExcelWriter from pandas import ExcelFile %matplotlib inline DiamondPrices = pd.read_csv(r'diamonds.csv') […]
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