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.
This course is prepared for Basic Learners.
What you will learn!
Key features from the Pandas Cheat Sheet
Python Data Analysis
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
Need to know before starting?
Python
Jupiter Notebook
anaconda
Excel's Row and Column Concept
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Students
762
Reviews
1,329
Answers
4.8
Rating
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Microsoft MVP(Python Developer Technologies)
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Curriculum
All
63 lectures ∙ (11hr 10min)
Course Materials: