A scatter plot is a method to display data that shows the relationship between two numerical variables. Each dot on the scatter plot can represent a single data point, with the x-axis representing one variable and the y-axis representing the other variable. By plotting the data points on a graph, we can visually analyse the relationship between the two variables.<\/p>\n\n\n\n
The plot.scatter() method in Pandas allows us to make scatter for our data visualisation needs.<\/strong><\/p>\n\n\n\n Following is the syntax of the plot.scatter():<\/p>\n\n\n\n Parameters:<\/strong><\/p>\n\n\n\n Now, let us look at how to use the method to draw scatter plots of our data.<\/p>\n\n\n\n We can simply use a DataFrame and then apply plot.scatter. To create a scatter plot from the DataFrame, we can use the plot.scatter() function and specify the ‘x’ and ‘y’ columns.<\/p>\n\n\n\n Let us look at an example:<\/p>\n\n\n\n Output:<\/strong><\/p>\n\n\n\n We can also customise our scatter to meet our needs. Pandas provide various options to customize the appearance of the scatter plot. We can modify the size, colour, and other properties of the data points to improve the visualization.<\/strong><\/p>\n\n\n\n Let us first see how to modify the size of the dots. To provide customised sizes for each dot, we can pass a sequence of scalars with the sizes. <\/strong>A sequence of scalars is similar to a list of integers.<\/p>\n\n\n\n See the Python code below:<\/p>\n\n\n\n Output:<\/strong><\/p>\n\n\n\n In the above example, we assigned different sizes to every dot based on a sequence of scalars<\/strong> [50, 100, 150, 200, 250]. The first dot will have a size of 50, the second dot will have a size of 100, and so on.<\/p>\n\n\n\n Now, let us learn how to change the colour of the dots:<\/p>\n\n\n\n Output:<\/strong><\/p>\n\n\n\n We can define various colours in the \u2018c\u2019 parameter of the plot.scatter method. In the example, we defined our scatter points to be red.<\/p>\n\n\n\n We can also use the traditional library for plotting graphs, matplotlib to plot scatter plots.<\/p>\n\n\n\n Matplotlib is a powerful library for data visualization and provides extensive customization options.<\/strong><\/p>\n\n\n\n Let us look at an example of how to draw a scatter plot using matplotlib:<\/p>\n\n\n\n Output:<\/strong><\/p>\n\n\n\nDataFrame.plot.scatter(x, y, s=None, c=None, **kwargs)<\/code><\/pre>\n\n\n\n\n
<\/li>\n<\/ul>\n\n\n\nCreating a Scatter Plot from a DataFrame<\/strong><\/h3>\n\n\n\n
import pandas as pd\n\n# Create DataFrame\ndf = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [2, 4, 6, 8, 10]})\n\n# Display the DataFrame\nprint('Original DataFrame:\\n', df)\n\n# Create scatter plot\ndf.plot.scatter(x='A', y='B')<\/pre><\/div>\n\n\n\nOriginal DataFrame:\n A B\n0 1 2\n1 2 4\n2 3 6\n3 4 8\n4 5 10\n<\/code><\/pre>\n\n\n![\"Creating](\"https:\/\/lh7-us.googleusercontent.com\/D3n8Cmwate0ZpP_QbBf1DnH3gIRyXP6tGJfr8rnVv1rVWnPpQi6-JkJ7msR0tjz5zGWosS8Y18XHIfOxBo0S51Yy7SGBBkKIVat55OhlEcqy5zOTUYeg3LzSD8I8AreWKA7Gi4cOp5Hxiihos00N-PI\")
Customising our Scatter Plot<\/strong><\/h3>\n\n\n\n
import pandas as pd\n\n# Create DataFrame\ndf = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [2, 4, 6, 8, 10]})\n\n# Display the DataFrame\nprint('Original DataFrame:\\n', df)\n\n# Create scatter plot with customized size\ndf.plot.scatter(x='A', y='B', s=[50, 100, 150, 200, 250])<\/pre><\/div>\n\n\n\nOriginal DataFrame:\n A B\n0 1 2\n1 2 4\n2 3 6\n3 4 8\n4 5 10\n<\/code><\/pre>\n\n\n![\"Customising](\"https:\/\/lh7-us.googleusercontent.com\/io18T49z4iLw2reCmrTQ1H1pZNgkZazKbYx9K9MzRiQPTUbiROB_pKTYCqfZdNeoKm9mcHWpKhBIbYsP2peSGviqo1AUJyyOQDFnmR9GE1B_AwZJUjYp31Armc1kpsdQHhwQywgpPFmkgX8sLGI2ygw\")
import pandas as pd\n\n# Create DataFrame\ndf = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [2, 4, 6, 8, 10]})\n\n# Display the DataFrame\nprint('Original DataFrame:\\n', df)\n\n# Create scatter plot with customized color\ndf.plot.scatter(x='A', y='B', c='red')<\/pre><\/div>\n\n\n\nOriginal DataFrame:\n A B\n0 1 2\n1 2 4\n2 3 6\n3 4 8\n4 5 10\n<\/code><\/pre>\n\n\n![\"Changing](\"https:\/\/lh7-us.googleusercontent.com\/VQ8mTXZUtLhgHmrYkTJqy4KnqBdIvXO8HD30R2F6CfYRFJgcA4zi1OTAWJ3_4Nz-O9_ttG07FPrYZk39gyLMbL8z8M-XjTC7tNdZ3dERY9NQpbswruMewmdQns5-9RP9IcvtuwOfcJ0iV74kU1zSb3I\")
Using Matplotlib to Create Scatter Plots<\/strong><\/h3>\n\n\n\n
import matplotlib.pyplot as plt\nimport pandas as pd\n\n# Create DataFrame\ndf = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [2, 4, 6, 8, 10]})\n\n# Display the DataFrame\nprint('Original DataFrame:\\n', df)\n\n# Create scatter plot using Matplotlib\nplt.scatter(df['A'], df['B'])\nplt.xlabel('A')\nplt.ylabel('B')\nplt.title('Scatter Plot')\nplt.show()<\/pre><\/div>\n\n\n\nOriginal DataFrame:\n A B\n0 1 2\n1 2 4\n2 3 6\n3 4 8\n4 5 10\n<\/code><\/pre>\n\n\n
![\"Create](\"https:\/\/lh7-us.googleusercontent.com\/Rq6GXSeZP_uthPNmg0wugPSukBybY7nqRTcTcIS-c1fZeRPvyJaz6vCY_BSBCFiLntYiBr2jFIvxQYn1qt1jN_HAOyKadMjk2yWV3WLTkVRBSH2hLNls15h5JUlDbdQXrhEG9D4hMLAVDRsMm6uEYdE\")
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