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the input file at which point I remove the customer from the master file.</p><p id="5f5a">These are just a couple of examples of using Excel & Python together. I have numerous others.</p><h2 id="dd0a">Web Scraping/Crawling</h2><p id="ac67">I have too many examples to cover here but I use several Python packages to web scrape ane web crawler: BeautifulSoup, Requests, Selenium, Scrapy, urllib.requests. These are my go-to packages but there are many others. I scrape to find leads for customers, classify websites, collecting pricing information. I have crawled many websites including Macy's and Nordstorm for a customer who needs their product listing to build a map.</p><h2 id="6d52">Application Development</h2><p id="8465">I have developed numerous applications for customers using Python mainly these days but have also developed applications using Java and C#. Some examples include a time management system, a cemetery contracting system, a point of sale system, a google purchase order system, and others. Application development is still quite lucrative if you can find the right gigs.</p><h2 id="f729">Natural Language Processing (NLP)</h2><p id="ff59">Sometimes people need to classify data and NLP is a great aid. You can even mix NLP with some machine learning. This is one of the more specialized skills that I might not try to tackle at first.</p><h2 id="06ba">Tutoring</h2><p id="1b83">Don’t forget tutoring. I don’t tutor much these days but have earned as much as $6000 per month tutoring. It’s especially profitable if you can find a group to tutor. I tutored a group of 6 MBA students to help them with their math-related classes. I charged each of them$ 50 per hour so I made $300 per hour and sometimes on Saturday I would work with them as much as 6 hours — could not handle more as I became fatigued. Math, Chemistry, SAT, and ACT are good as well. SAT and ACT for groups in particular. I have also tutored Python and C#.</p><h2 id="fb38">Recommended Packages</h2><p id="3180">Finally, I thought it would be good to provide a list of recommended packages that any Python developer should know to grow his business.</p><p id="86c3">— os</p><p

Options

id="8728">— Pathlib</p><p id="d4ba">— glob</p><p id="da16">— pandas</p><p id="c8d5">— Beautifulsoup</p><p id="b539">— Requests</p><p id="da80">— Selenium</p><p id="9238">— c</p><p id="756a">— NLTK (Natural Language Toolkit)</p><p id="2c47">— FuzzyWuzzy (great if you need to match similar data)</p><p id="cd29">— NumPy (great for more math-oriented use cases)</p><p id="ce21">— pickle (Creating pickle files helps with large data sets)</p><p id="119e">— time</p><p id="f2c7">— PDFMiner for working with PDF files (it’s better than PyPDF2)</p><p id="d80d">— Sklearn</p><p id="a281">Within pandas, you should learn how to merge, join, concatenate, rename columns, extract data, query data, search data, clean data. Of course, you will need to know how to read CSV and Excel files at a minimum and sometimes pickle files. I have tried Parquet files but they don’t seem to work well — at least not for me. Pandas has pretty good documentation:</p><div id="af66" class="link-block"> <a href="https://pandas.pydata.org/pandas-docs/stable/"> <div> <div> <h2>pandas documentation - pandas 1.3.4 documentation</h2> <div><h3>The reference guide contains a detailed description of the pandas API. The reference describes how the methods work and…</h3></div> <div><p>pandas.pydata.org</p></div> </div> <div> <div style="background-image: url(https://miro.readmedium.com/v2/resize:fit:320/)"></div> </div> </div> </a> </div><p id="afe8">Also, it is important to understand how to use lists, tuples, sets, and dictionaries. I might start here first if I were a newbie. Understand and use the datetime package.</p><p id="ea46">These are just a few ideas to get you on the right track to building a consistent income using Python and other resources. Hope this helps.</p><p id="147e">Thank you for reading.</p><p id="8ed0"><i>More content at <a href="http://plainenglish.io/">plainenglish.io</a>. Sign up for our <a href="http://newsletter.plainenglish.io/">free weekly newsletter here</a>.</i></p></article></body>

$3000+ Monthly with Python, Excel & Tutoring

Learn how to easily make $3000 or more monthly.

You can make $3000 or more monthly with Python, Excel, and Tutoring. Read the entire documentation — at the end, I share the basic toolset to build your business and grow as an entrepreneur using Python and other resources.

Excel

Many users don’t know that Excel is a gold mine for extra income. I have a recurring gig with Excel that earns me around $800. It takes me about 2 hours to complete. The project is a medical company that needs to calculate the profit based on the procedure and the doctor fulfilling the request. It’s an annual job so every year I get a little Christmas present. It uses some rather complex formulas but I just need to create a template to run the next year's formula. Of course, I could revamp his sheets so that they would not have to be updated each year but sometimes he adds new physicians. I am happy to collect the $800 each year — might have to raise the price this year due to inflation.

Excel & Python

Sometimes, I have partnered Excel and Python. I run the job in Python but create outputs in Excel. I have a customer that pays me a retainer to run this little job that takes me about 5 minutes or so to complete. The retainer is only $50 but it is a quick and easy job. I merge a new monthly with an existing Excel document. I have to use Pandas and Python to clean the new file before I append to it the existing file.

I have another gig with the same customer who needs to synchronize past-due invoices. Syncta generates a list of past-due invoices for him but he has to track calling up his customers for past-due invoices. First, I created a master file for him that adds notes and a date column. He downloads his input file. I sync it with the master file. If a customer has paid he is no longer on the input file at which point I remove the customer from the master file.

These are just a couple of examples of using Excel & Python together. I have numerous others.

Web Scraping/Crawling

I have too many examples to cover here but I use several Python packages to web scrape ane web crawler: BeautifulSoup, Requests, Selenium, Scrapy, urllib.requests. These are my go-to packages but there are many others. I scrape to find leads for customers, classify websites, collecting pricing information. I have crawled many websites including Macy's and Nordstorm for a customer who needs their product listing to build a map.

Application Development

I have developed numerous applications for customers using Python mainly these days but have also developed applications using Java and C#. Some examples include a time management system, a cemetery contracting system, a point of sale system, a google purchase order system, and others. Application development is still quite lucrative if you can find the right gigs.

Natural Language Processing (NLP)

Sometimes people need to classify data and NLP is a great aid. You can even mix NLP with some machine learning. This is one of the more specialized skills that I might not try to tackle at first.

Tutoring

Don’t forget tutoring. I don’t tutor much these days but have earned as much as $6000 per month tutoring. It’s especially profitable if you can find a group to tutor. I tutored a group of 6 MBA students to help them with their math-related classes. I charged each of them $50 per hour so I made $300 per hour and sometimes on Saturday I would work with them as much as 6 hours — could not handle more as I became fatigued. Math, Chemistry, SAT, and ACT are good as well. SAT and ACT for groups in particular. I have also tutored Python and C#.

Recommended Packages

Finally, I thought it would be good to provide a list of recommended packages that any Python developer should know to grow his business.

— os

— Pathlib

— glob

— pandas

— Beautifulsoup

— Requests

— Selenium

— c

— NLTK (Natural Language Toolkit)

— FuzzyWuzzy (great if you need to match similar data)

— NumPy (great for more math-oriented use cases)

— pickle (Creating pickle files helps with large data sets)

— time

— PDFMiner for working with PDF files (it’s better than PyPDF2)

— Sklearn

Within pandas, you should learn how to merge, join, concatenate, rename columns, extract data, query data, search data, clean data. Of course, you will need to know how to read CSV and Excel files at a minimum and sometimes pickle files. I have tried Parquet files but they don’t seem to work well — at least not for me. Pandas has pretty good documentation:

pandas documentation - pandas 1.3.4 documentation

The reference guide contains a detailed description of the pandas API. The reference describes how the methods work and…

pandas.pydata.org

Also, it is important to understand how to use lists, tuples, sets, and dictionaries. I might start here first if I were a newbie. Understand and use the datetime package.

These are just a few ideas to get you on the right track to building a consistent income using Python and other resources. Hope this helps.

Thank you for reading.

More content at plainenglish.io. Sign up for our free weekly newsletter here.