본문 바로가기

Study Note58

Join, Merge, Concat, Append, and Pivot table 1. Using the join MethodThe join method in pandas is used to combine two dataframes based on their index. Here is the syntax: DataFrame.join(other, on=None, how='left', lsuffix='', rsuffix='', sort=False) other: The dataframe to join with.on: Column or index level names to join on. Default is the index.how: Type of join to perform ('left', 'right', 'outer', 'inner'). Default is 'left'.lsuffix: S.. 2024. 5. 23.
The difference between deep learning and machine learning The difference between deep learning and machine learning Artificial Intelligence: Human capabilities and functions -> ComputerMachine Learning: Learns patterns, rules, and characteristics on its own using large amounts of data. (Data-dependent - if the data is wrong, it will fail) / Advantage: Just provide the data [because it learns by itself] -> Data must be very well refined.Deep Learning: D.. 2024. 5. 21.
With CTE I've been solving CodeKata questions and have already completed up to question number 76. While solving these questions, I wanted to practice using WITH CTE. Mastering WITH CTE seems like it will allow me to simplify complex code in various ways.  What is a CTE?A CTE (Common Table Expression) is a temporary result set defined within the execution scope of a single SQL statement. It improves the.. 2024. 5. 20.
Seaborn plot (Scatter, Hist, and Box) Today, I plan to practice again by using Seaborn to recreate the plots I made last time.  Seaborn is a Python package for data visualization, built on top of Matplotlib. It provides a high-level interface for creating attractive and informative statistical graphics.Seaborn is used to visualize statistical data, particularly to explore relationships between variables. It offers a wide range of pl.. 2024. 5. 16.
Library (Pandas, Seaborn, Matplotlib, Numpy) - Iris Data When using Python, in addition to basic functions, we need to utilize various libraries. Especially, Pandas, Seaborn, Matplotlib, and Numpy are the most essential libraries when performing data analysis.  1. Pandas:   - Purpose: Pandas is used for data manipulation and analysis. It provides data structures to efficiently store and manipulate data. Its main data structures are Series (a one-dimen.. 2024. 5. 14.
The Pearson correlation coefficient The Pearson correlation coefficient is a statistical method used to measure the linear relationship between two variables. It typically describes how two variables move together. The Pearson correlation coefficient ranges from -1 to 1, and it is interpreted as follows:- Close to 1: Indicates a strong positive linear relationship between the two variables. As one variable increases, the other var.. 2024. 5. 13.

티스토리툴바