Review of Python Courses (Part 21)
Posted by Mark on January 26, 2021 at 07:10 | Last modified: February 8, 2021 14:22In Part 20, I summarized my Datacamp courses 59-61. Today I will continue with the next three.
As a reminder, I introduced you to my recent work learning Python here.
My course #62 was Time Series Analysis in Python. This clearly has potential applications for investment returns, but in the end I wasn’t totally sure what those might be. The course covers:
- Introduction to the course
- Correlation of two time series
- Simple linear regressions (in statsmodels, numpy, pandas, scipy)
- Autocorrelation (convert index to datetime)
- Autocorrelation function (from statsmodels.graphics.tsaplots import plot_acf; from statsmodels.tsa.stattools import acf)
- White noise
- Random walk (from statsmodels.tsa.stattools import adfuller)
- Stationarity
- Introducing an AR model (from statsmodels.tsa.arima_process import ArmaProcess)
- Estimating and forecasting an AR model
- Choosing the right model (from statsmodels.graphics.tsaplots import plot_pacf)
- Estimation and forecasting an MA model
- ARMA models
- Cointegration models
- Case study: climate change
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My course #63 was Intermediate Predictive Analytics in Python. This course covers:
- The basetable timeline
- The population
- The target
- Adding predictive variables
- Adding aggregated variables
- Adding evolutions
- Using evolution variables
- Creating dummies (avoiding multicollinearity)
- Missing values (list comprehension)
- Handling outliers (from scipy.stats.mstats import winsorize)
- Transformations
- Seasonality
- Using multiple snapshots
- The timegap
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My course #64 was Building and Distributing Packages with Conda. This is another shell-related course I found hard to absorb since I do very little in the shell. I’m not the only newbie who feels this way, either. This was a recent post to the group:
> I have been doing Python courses for a while but now I actually wanna try some real
> live data on my laptop and I am not sure on how to install all of the needed stuff
> (pandas, numpy, etc.). I have downloaded the latest Python version and the PyCharm
> editor but… [the courses] do not really have anything to show you how to actually
> make the rest of the things work for inexperienced people such as myself.
I downloaded Spyder IDE, which has met most of my needs. It crashes sometimes and gives repetitive errors upon start-up, though, which are both quite annoying. I’ve also had mixed results downloading some libraries like Backtester.
Speaking of Anaconda, or conda for short, my 64th course covers:
- Anaconda Project
- Anaconda Project specification file
- Anaconda Project commands
- Python module and packages
- Python package directory
- Conda packages
- Conda package dependencies
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I will review more courses next time.