News / Blog: #glossary

What is Pandas?

Pandas is a Python library used for data analysis and manipulation. It provides powerful functions for importing and processing data from various data sources, including CSV files, Excel files, databases and web APIs.

The core components of Pandas are two data structures: Series and DataFrames. Series is a one-dimensional data structure, similar to a list or array, while DataFrames are a tabular data structure consisting of columns and rows, similar to a table in a database.

Pandas allows you to filter, sort, group, merge, transform and clean data. It also supports the creation of pivot tables and time series analysis. Pandas also allows users to handle missing values and interpolate missing data.

Pandas is often used in conjunction with other libraries such as NumPy, Matplotlib and Scikit-learn to perform complex data analysis. Due to its powerful features and ease of use, Pandas has become one of the most popular libraries for data analysis in Python.

What is NumPy?

NumPy (Numerical Python) is a Python library that supports arrays and matrices of numerical data and performs basic operations on this data. NumPy is designed to improve the performance of Python when working with large amounts of data and to perform mathematical operations on this data quickly and efficiently.

NumPy provides many useful functions, such as linear algebra, Fourier transform, random number generation, mathematical functions and more. It is often used in combination with other libraries such as Pandas, Matplotlib and Scikit-learn to perform complex data analysis and simplify scientific calculations.

Thanks to its rich features and ease of use, NumPy has been widely used in the scientific community and is one of the most important libraries for data analysis in Python.

What is an editorial plan?

An editorial plan is a document created by an editor or editorial team to plan the content to be published in a specific time period. An editorial plan includes a list of content to be published, a sequence of publication dates, and a list of authors who are responsible for the content.

What does a Data Scientist do?

A Data Scientist is an expert in analyzing large amounts of data. He or she can process data from different sources and turn it into valuable knowledge using algorithms and statistical methods. He or she presents data in a visual form in order to identify trends and correlations and gain valuable insights. Furthermore, a Data Scientist can also make predictions and recommendations based on the analysis of the collected data.

What is Data Science?

Data Science is the collection, analysis and interpretation of data. It involves the application of mathematical methods, statistical models, and machine learning techniques to identify trends and pattern recognition in data and make predictions. It is an interdisciplinary discipline that requires both conceptual and technical skills.