Pandas beginner exercises on Jupyter notebook
Look at plotting, date ranges and other niceties in Python pandas
What is Python Pandas?
Pandas is a data science toolkit created by Wes McKinney in 2008. It has exploded in popularity ever since. You have enormous weight behind it with lot of corporations using it for serious computations and representation of various metrics, samples and more.
This is not only a data science thing but also useful for everything involving data and analyzing trends and historical data.
What is Panel data?
Panel data is any two dimentional representation of two axes, X and Y. You could have series on both axes. Pandas understands series as a data type, derived from another Python module numpy.
You can also create date ranges for time series as we do in our example below.
What is a series?
A series is nothing but a mathematical progression of integers. You could have time stamps or even column names to serve as series members.
Pandas supports a wide range of possibilities for constructing two dimensional data and you can easily create a transpose of the matrix if you want.
You can create running averages or compute mean, standard deviation and other computations on historical data to measure and assess some entity.
What is a timeseries?
A time series is a representation of data against time stamps. Pandas allows timestamps upto the granulality of milliseconds. You can specify the intervals based on days or months or biz days , you can even specify periods between date ranges.
By populating the data samples for each time stamp you can easily create tabular views and graph plots, usually just line graphs. Pandas uses matplotlib for it.
Code sample and demo
Jupyter notebook is available here. We have a sample of using Python dictionary to create a data frame. You can also make it from third party CSV or JSON files.
Pandas has multiple connectors using which you can import and export panel data.
Conclusion
Pandas is really useful for quick plot or tabular view of some important metric in daily life. It is the primary engine for several data science projects.
Moreover Jupyter notebook is also heavily used by physicists and people working on Julia and R as well as Python. We have seen Jupyter notebook several times before.
You are welcome to download this and get things going inside your browser by installing Jupyter notebook on your Linux/Windows/Mac.
Answer
What is computational intelligence?
Computational intelligence (CI) is a branch of artificial intelligence (AI) that involves creating systems and algorithms that can learn from data and make decisions based on what they've learned. CI is a rapidly evolving field of computer science that aims to develop techniques and algorithms to enable machines to solve complex problems.
Complexica
Computational Intelligence
CI is the theory, design, application, and development of computational paradigms that are motivated by biology and linguistics. The goal of CI is to create a new approach for analyzing and creating flexible information processing of humans, such as sensing, understanding, learning, recognizing, and thinking.
CI is a set of nature-inspired computational methodologies and approaches. Some of the main principles of CI include: Fuzzy logic, Neural networks, Evolutionary computation, and Probabilistic methods.
The main applications of CI include: Computer science, Engineering, Data analysis, and Bio-medicine.
Question
What is a Pandas dataframe?
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