Pandas has so many uses that it might make sense to list the things it can't do instead of what it can do. This tool is essentially your data’s home. Through pandas, you get acquainted with your data by cleaning, transforming, and analyzing it. For example, say you want to explore a dataset stored in a CSV on your computer. Pandas will extract the data from that CSV into a DataFrame — a table, basically — then let you do things like: Calculate statistics and answer questions about the data, like What's the average, median, max, or min of each column? Does column A correlate with column B? What does the distribution of data in column C look like? Clean the data by doing things like removing missing values and filtering rows or columns by some criteria Visualize the data with help from Matplotlib. Plot bars, lines, histograms, bubbles, and more. Store the cleaned, transformed data back into a CSV, other file or database Before you jump into the modeling or the complex visualizations you need to have a good understanding of the nature of your dataset and pandas is the best avenue through which to do that.
Type of Material:
Open (Access) Textbook
Recommended Uses:
Self-paced learning or tutorial on Pandas.
Technical Requirements:
Basic programming and data structure knowledge
Identify Major Learning Goals:
Upon completion of this material, learners should be able to:
1. describe the basic concept of pandas in python
2. implement computer programs using pandas
3. apply pandas to solve different data manipulation problems
In summary, it goes over the essential bits of information about pandas, including how to install it, its uses, and how it works with other common Python data analysis packages such as matplotlib.
Target Student Population:
College Upper Division, Graduate School
Prerequisite Knowledge or Skills:
Basic programming knowledge
Content Quality
Rating:
Strengths:
- It describes the use of the basic commards in Pandas.
- The commards and descriptions are correct and the level is appropriate for the beginners.
- The codes provided are accurate too, so the learners need only to copy and paste the codes provided into their own jupyter notebook, the expected results could be given.
- Furthermore, it introduces how to apply functions, which is a powerful feature in data manipulation. It also mentions how the data to be converted from dataframe to some file formats, including csv, json and sql database. The brief plotting is also well presented.
In summary, the materials is very comprehensive and informative. It includes the foundamental knowledge about pandas for data manipulation in python. The content is accurate and appropriate for beginners. It contains sufficient number of examples to illustrate the ideas.
Potential Effectiveness as a Teaching Tool
Rating:
Strengths:
- The learning goal of the web site is clear while a specific topic, the learners will find the significance after the results.
- It starts with basic elementry teams in Pandas, assuming the learners having no background on python programming. They can learn Pandas from the installation of the package.
- The web site expects the learner to view the contents from the begining to the end, so the learners need the follow the sequence; otherwise, they may get lose.
- To promote the conceptual understanding, in addition to introducing the commards and the outputs in Python, it also introduce the statistical meanings of the the commards, such as corr.
In summary, the learning objectives of the material are very clear. It focues on the major and common techniques in pandas with examples. The diagrams can help learners to grasp the concepts easily. It can be used as a textbook or tutorial workbook in face-to-face classes.
Ease of Use for Both Students and Faculty
Rating:
Strengths:
- The web page gives a self-contained learning content on Pandas. Files should also be available in the link to GitHub, such as the csv file for the read_csv and read_json. - Even though the website does not comes with fancy animations or videos, the learners can be able the follow the contents step by step.
- The web page gives a self-contained learning content on Pandas. Files should also be available in the link to GitHub, such as the csv file for the read_csv and read_json. - Even though the website does not comes with fancy animations or videos, the learners can be able the follow the contents step by step.
In summry, as an open textbook, the material is very easy to use. It shows the steps to install python and pandas, which is very helpful for beginners. The diagrams are effective to illustrate the concepts and visually appealing.
Concerns:
There is very little interaction and exercises for learners.
It will be better if some index will give so that learners can easily identify a specific topic.
Creative Commons:
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