Mastering Data Analysis and Visualization with Just Two Documents
When you use Pandas for data analysis, preprocessing, machine learning, and deep learning, you tend to use only the functions you use frequently.
There is a Pandas Cheat Sheet that collects and organizes only these essential contents. For those who get tired of learning Pandas from a thick book, we will teach you Python Pandas with just two pages of documents. Learn the core functions of Pandas with the cheat sheet provided in the official Pandas tutorial.
Data preprocessing for machine learning and deep learning
Data Visualization
Crawling, preprocessing, analyzing, and visualizing the Seoul City COVID-19 site using Pandas
Python Pandas Data Analysis, the essentials all at once!
In just two documents Pandas data analysis Can you solve it?
There is a library called Pandas that allows you to use Excel-like functions in Python.
Excel can't handle it Large-scale data processing is also OK.
Pandas is for data analysis and preprocessing. It is a Python data analysis library.
When doing data analysis, preprocessing, or visualization with Python Pandas, you will mainly use the functions that you use most. And there is a cheat sheet that organizes these core functions into just two pages.
However, if you look at a cheat sheet that only contains such core contents, you may be at a loss as to what content to practice and how to practice it. In this lecture, we will explain only the core contents of the cheat sheet and guide you through how to easily use complex Matplotlib with Pandas. Let's try it together.
Who would benefit from learning this?
data analysis, Required for ML/DL I want to do preprocessing People who do it
Large volume of data Open it with Excel The file won't open Those who were confused
Using Excel do data analysis In complex formulas Tired person
Various in Excel I implemented the formula, but It's slow People who had to work overtime
📣 Check your player knowledge!
Prerequisite knowledge of Python and Jupyter Notebooks, Anaconda, and row/column concepts in Excel is required.
Focusing on official documents Easy, fast and accurate.
One, in the Jupyter notebook Using docstring
You don't need to memorize all the methods. The functions used are fixed. In this lecture, I will teach you how to practice by searching the official documentation in Jupyter Notebook so that you can learn on your own by looking at the help and documentation.
2. Pandas data visualization How to do it twice as well!
Do you know which graph is appropriate for which data? In this lecture, we will look at the differences and usage of bar graphs, frequency distribution tables, histograms, and normal distributions. In addition, we will explain various Python visualization methods and options through the official Pandas documentation.
Bonus, visualize Series and DataFrame data!
Additional updates! Perfect for practical use Data analysis project.
We will analyze the Seoul City COVID-19 Status Site using Pandas from data crawling to preprocessing, analysis, and visualization. You can analyze the content learned in just two documents into a project similar to the actual work . (Section 13)
First, we directly analyze data that we frequently encounter in our daily lives through the news.
Which district has the most confirmed cases?
Which hospital treated the most confirmed cases?
Are there any hospitals that people are frequently transferred to by district?
Which district has the most confirmed cases from overseas?
How can I preprocess texts from multiple countries, such as Europe, South America, etc?
How much difference will there be in the number of confirmed cases coming from overseas from month to month?
Second, understand and practice data preprocessing methods using Pandas.
How do I get the year, month, day, day of the week, and week number from a text date?
How can we calculate the cumulative number of confirmed cases using confirmed case status data?
What is the difference between groupby, crosstab, pivot, and pivot_table, and which function is appropriate to use?
3. Understand the data structure of data frames and series and process them into a form suitable for analysis.
How should I create a data frame for drawing a graph using Pandas' plot?
How can I change my dataframe if I want to display values in different colors based on their categorical values in the graph?
Is there any way to convert a series to a dataframe?
Python Visualization & Analysis Examples, Check it out for yourself in class!
Created this course If you are curious about the knowledge sharer? 👩💻
Knowledge Sharer Park Jo-eun X Inflearn Interview
Recommended for these people
Who is this course right for?
Anyone who wants to do preprocessing for data analysis, machine learning, and deep learning in Python
If you were confused because a large amount of data could not be loaded when opening it in Excel
Are you tired of Excel's complicated formulas?
If you implemented various formulas in Excel but had to work overtime because the speed was slow
As a beginner, I think this is a great lecture that will help you learn the overall concept of Pandas and learn thoroughly how to use it for actual analysis. I have taken several lectures on Pandas, but I think this is the only lecture that explains the details one by one with such quality. I will review it again and apply it to actual business data and analyze it. Thank you so much for making such a great lecture!!
Overall, it was a good course. I studied Pandas on my own with a book and applied for this course for the purpose of repeated learning and application of Pandas.
The Pandas cheat sheet course was actually not that great. It won't be of much help to those who are new to Pandas, new to Python, or very beginners. It's okay as a YouTube video, but it's a bit disappointing as a paid lecture.
The Seoul City Corona Analysis course was good. It was a very useful part for me who studied the basics of Pandas because I was able to practice how to process data by applying Pandas to obtain the desired form and results.
And the tips given here and there were also very helpful. Like shift-tab, or using ? after a function to see the dot string... I think these are great tips...
Summary in one line: I don't recommend it to those who are just starting out with Pandas, but I highly recommend it to those who know a little about Pandas.
It's a good curriculum. Even a beginner like me could see the operating principles and results at the same time. What I like the most is the Q&A part. If there's something you don't know, you can ask the teacher questions and get answers right away. And the teacher's voice has such a good wavelength that it's easy to concentrate.
After graduating from the Department of Statistics and working as a data analyst, I quit my job and am studying data analysis using Python through Park Jo-eun's lecture. It was interesting to follow the lecture because it was easy to understand using timely data rather than obvious example data. I also watch YouTube a lot. Thank you!