To grab random sample from a dataset in Python, you can use the pandas library. Assuming your dataset is stored in a pandas DataFrame, you can use the sample method to randomly select rows. Here’s an example: In this example, n=5 specifies the number of rows to sample, and random_state is set to ensure reproducibility.
In Python, the warnings module provides a way to handle warnings emitted by the Python interpreter or third-party libraries. When you use import warnings, you can control how warnings are displayed or handle them programmatically. Here are some common use cases:
To save a Google Colab notebook as an HTML file, you can follow these steps: Replace the path and your_notebook_name.ipynb with the actual path and name of your Colab notebook in your Google Drive. Now you have an HTML version of your Google Colab notebook that you can save, share, or submit.
You can use the subplot function in Matplotlib to create multiple plots arranged in a grid. To put two plots on top of each other, you can use the following approach: In this example, plt.subplot(2, 1, 1) creates the first subplot in a 2-row, 1-column grid, and plt.subplot(2, 1, 2) creates the second subplot beneath…
Gaussian distribution, also known as a normal distribution, is a continuous probability distribution that is symmetric around its mean, forming a bell-shaped curve. It is a fundamental concept in statistics and probability theory. The shape of the distribution is characterized by its mean (average) and standard deviation. The probability density function (PDF) of a Gaussian…
In pandas, you can give a specific sorting order to categorical values by creating a categorical variable with an ordered category. Here’s an example: In this example: This can be useful when you want to ensure that certain operations, such as sorting or plotting, take into account the natural order of the days of the…
To cap or clip outliers in a column, you can use the clip method in pandas. The clip method allows you to set a minimum and maximum threshold for the values in a DataFrame or a specific column. Here’s an example: Clipping is a simple method, and it’s important to consider the impact on your…
hen dealing with missing data of type categorical, several methods can be used to impute the missing values. Here are some common approaches: The choice of imputation method depends on the nature of the data, the underlying patterns, and the goals of the analysis. Always consider the context of the data and the potential impact…
leaning a dataset involves handling missing values, correcting errors, and preparing the data for analysis. Here are common steps to clean a dataset using Python and pandas: Always document the steps taken during the cleaning process for transparency and reproducibility. Additionally, it’s crucial to thoroughly understand the context of the data and the goals of…
n Pandas, pd.set_option(‘display.float_format’, …) is used to set the formatting options for floating-point numbers when they are displayed in the console or output. It allows you to customize how floating-point numbers are presented, including the number of decimal places, scientific notation, and other formatting details. In this example, the pd.set_option(‘display.float_format’, ‘{:,.2f}’.format) line sets the floating-point…
