This article explains the role of python in data analysis. Data Analytics helps to understand the various trends and Company data.
Python is a programming language that helps in Data Analytics. Today we will learn how python helps analyze data.
What is Data Analytics?
Data Analytics analyzes raw data for trends. Data Analytics is a broad field with a set goal. There are basically four types of data analysis:
Descriptive Statistics: Descriptive Statistics refer to the process of answering questions about what happened. It is best used to provide an explanation of the outcome to participants. In this process, relevant data is collected and analyzed, and then the data is visualized. Descriptive statistics provide insight into what is being done.
Diagnostic statistics: Diagnostic statistics refer to the process of answering questions about why things happened. They collect descriptive analysis and dig deep into the data to find the root cause.
Predictable statistics: Predictable statistics refer to the process of answering questions about what will happen in the future. This process uses previous historical data to identify trends in the data and determine whether it will reappear or not. Guessing statistics provide insight into future trends. The process uses a variety of machine learning and mathematical methods such as deceleration, sensory networks, and cutting trees.
Descriptive statistics: Descriptive statistics refer to the process of answering questions about what to do. Through predictable analysis, data-driven decisions are made. It helps to quantify the results by looking at previous data. Data Analytics is something that should be needed in the banking and financial sector.
Data Analytics helps detect and prevent fraud, to improve financial institutions’ efficiency.
Data Analytics is divided into 4 steps:
- Data Mining
- Data Management
- Mathematical Analysis
- Data Presentation
What is Python?
Python is a growing programming language that is used in both web development and design and is used to design software programs. It is a very easy to learn and use language. It has many advantages. It is used in Practical Learning, Mechanical Learning, and In-Depth Learning.
How does Python help with Data Analytics?
To use Python for Data Analytics, you must have a good knowledge of Matplotlib and CSV. Then, you need to install the panda that can be installed using the following command;
pip install pandas
Create a data framework for pandas. Then read the data stored in the CSV format files. Then import the data into the panda. Identify data using mathematical labels and pandas. And this is how the pandas are organized.