Python, with its flexibility, ease of learning, and a large developer community, has transformed the field of data analysis. In this article, we will learn about data analysis using Python.

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

However, in recent years the open source community has developed increasingly-sophisticated data manipulation, statistical analysis, and machine learning libraries for Python. We are now at the point ...

Whether you’re working with sales data, employee performance metrics, or customer insights, Python in Excel offers a smarter, more efficient way to handle external data.

Learn how B2B sales organizations are looking to artificial intelligence and data analytics for help with sales forecasting.

Useful Libraries for Data Analysis Whenever I start a data analysis project, I like to have at a minimum the following libraries installed: Requests. Matplotlib. Requests-html. Pandas.

Big Data is the biggest game-changing opportunity for marketing and sales since the Internet went mainstream almost 20 years ago. That statement often prompts vigorous head nodding from executives ...

import pandas as pd import statsmodels.formula.api as smf First, fetch the data needed for style analysis of equity funds. Obtain the unique tickers for the funds you plan to analyze.