/peteyBiz

Primary LanguagePython

Purpose

To help the love of my life out with very cool data analysis.

You will need

  • a very basic fluency in navigating the command line
  • Python (this tool was tested on Python version 2.7.16)
  • Git (usually pre-installed for Mac these days, but you will be prompted to install if not)

How to Use

  1. Open a command line interface using your application of choice (e.g. Terminal or PuTTY)
  2. Navigate to the directory that contains your CSV file(s)
    • 🤷‍♂️ Don't know how? You won't need to know much for this tool, so check out a basic tutorial!
    • Hint: ls, cd, and relative paths are your friends.
  3. Clone this repository (repo, for short) once you've made it to your directory containing the relevant CSV file, like so: 
    git clone https://github.com/haejinjo/peteyBiz.git
    • If you ls, you will notice that running this git command created a directory that wasn't there before! Let's look into it!
  4. Navigate into the newly generated repo directory 
    cd peteyBiz
  5. Once in the repo directory, copy-paste your CSV file from this cloned repo's parent directory like so: 
    cp ../yourFilenameShouldBeHere.csv .
    • Notice that the cp command takes two arguments: A source and a destination filepath.
    • As you might've discovered, .. means the previous or parent directory and . means the current directory, the latter of which serves as the "destination" in this case.
  6. Run my program using the python command: 
    python addRowCounts.py -i INPUT CSV FILE -c RELEVANT COLUMN NAME [--sort]
    • Note on -i: Since you are already in the directory where a copy of your file lives, you can just type the filename itself as an argument
      • Example: python addRowCounts.py -i someDataset.csv -c MAIDEN_NAMES
      • Normally, you'd have to write out a relative path
    • Note on -c: Make sure you reproduce the exact name of the column whose counts you want inserted as a new column.
    • Warning: If you run this command multiple times on the same input CSV file, the output file will be overwritten.
  7. If you ls, you should now see a CSV file ending in "_counted" that wasn't there before. 👋💩

🆘 Remember, if you ever forget what the program does or how it works, just run the following command:

python addRowCounts.py {-h | --help}

Development Process

  1. Create dummy CSV file data with 100 records based on what I glanced at on Petey's work using this nifty tool, given the following inputs:

    • Keywords: hash, first, last
    • Names: hashed_user_id, first_name, last_name

  2. Manually replace certain lines with duplicate rows (could've done this with some Math.random thing to automate the process, but I'm lazy and dumb sometimes)

    👁️ Example Dummy CSV Data 👁️ 
       hashed_user_id,first_name,last_name
   7355f6711abfe07488b36d89e296e0a271248de4,Louise,Castillo
   6b8085fa5423665fd2a250ce1da7e423aa8ffccb,Cameron,Fletcher
   00d2e06e75391fb0e46d0b90655f40ee83f221a2,Mollie,Reese
   00d2e06e75391fb0e46d0b90655f40ee83f221a2,Mollie,Reese
   d5eff30b51825ea042dd3aed25db9e94bcbf5aaf,Mitchell,Hudson
   f43b4772d4527f43ca880c6b9d9039b5e3f5ffd7,Vera,Scott
   7feef75ac3c189116e69c5dd28e35ea931c84b8b,Patrick,Mack
   58641dba0625ab5617f0f76b255eb3142a7935f9,Hettie,Ward
   b585a94d357b8cd1f86963d3d618f9de0a114360,Minnie,Ramos
   e8480f7a22cba933d2fb014f8c2be92e692ad86f,Andre,Perez
   6c07449a6de00f03fe32a7b2f2114b29197362b5,Lester,Lane
   00d2e06e75391fb0e46d0b90655f40ee83f221a2,Mollie,Reese
   58641dba0625ab5617f0f76b255eb3142a7935f9,Hettie,Ward
   9d61ed249f87685c9e11f096d0c3a799ca0ea48b,Dorothy,Butler
   7d6ed67d85ee64fda624116bec9ae7da9eb64d0c,Leroy,Boone
   8c506576c593141f5fccdf8aaec144a6760a1680,Vincent,Singleton
   7feef75ac3c189116e69c5dd28e35ea931c84b8b,Patrick,Mack
   c63e64513775e93af81ab3839a809d5e8ff1ca77,Francisco,Waters
   3edb4823e792d621215e335715a03cadff8ab3a9,Ernest,Sims
   f4e40992f5cd461e33c77cd856156a88d48799db,Mabel,Vasquez
   35c7b045ea2be5f911a82ed610ac9770e1fa159e,Warren,Dixon
   e0440fc95d8da90a3d6ef8be29945d82cb67a3d8,Dollie,Wilkins
   5adbb03145da3f1e649b29791b1713d385854d51,Sadie,Maldonado
   0eee8c0b7d9baf3752ba6738b9554bd3036f3965,Antonio,Chambers
   52f0a6d9273983c70cebab81fed2543064773366,Leonard,Buchanan
   0edcedff4a55c3adf73342446a55f4bc0951c94f,Julian,Parsons
   2cb4ab1140da07a2a158f70219c593106bbb4799,Flora,Lucas
   7feef75ac3c189116e69c5dd28e35ea931c84b8b,Patrick,Mack
   6f085a70b9d0a4315ac976e35e1e4ddd091ea995,Nelle,Poole
   f90e04d1d2d3cf9d3cc06967eee504152fe02c81,Rosa,Jenkins
   f4e40992f5cd461e33c77cd856156a88d48799db,Mabel,Vasquez
   9adb7dd2541533201533da5f5982b2fd88e07e68,Lucile,Parks
   3ec9a427cc008d7c0aeca5134c38fb7e1ad53bf1,Maud,Harrington
   294195215e4a93c7ab08ddcf1c70f16ffe316fdb,Adele,Bennett
   841a7f7ff82d1504ce101c5c714cd1249e793ef3,Jon,Tran
   568febb6d8929400c4116fa86cbc6fd061e0277e,Julia,Frazier
   39969d39a41111c6810c72ae55a5a80dedda0ad9,Leo,Gomez
   a1ce14e19e4fa00b02912b258e1997f958964b5e,Ida,Morgan
   3cdbdf539d6a1c4573b1432beb0c22defddd54ee,Irene,Spencer
   196dfdef48ab074c6af49ddf8c4c979ef420ef38,Juan,Lowe
   68973378b3211fb1aff7bfa9feb6bd49962bf8ee,Delia,Myers
   b4774cbded39aeb304051fba9a0d7b735c9a3db2,Charlie,Hardy
   89e40a5debc16f5e9a53e5359f2d63b518cad693,Clyde,Shelton
   3b54fb98cc6b6a1f02d4c7de6acfafd189de486e,Virginia,Warner
   a11ab8c0bf8ff15e6d6fe5217f9dfb95143c5b9e,Roger,Tate
   31a4857a1a57690293555793c6a1d525e5ce86f1,Leon,Henry
   5d0e33b618666ad0d21333c03f175f993f6aaf42,Winifred,Burgess
   5b09fd0a564f7af9b76d7733834745481ec9423d,Seth,Roy
   2c26eeab240290ea3232147057cf88cccc726ebe,Edna,West
   eab4bdbb818f2b55b59a0db64326edc8c6a9ea32,Irene,Powers
   416c5d812f55873533e6ef9aac5ddf8a34ad178e,Emily,Cortez
   61bd659b036b79c3df1de83508fbef7d673659cc,Wayne,Webster
   58641dba0625ab5617f0f76b255eb3142a7935f9,Hettie,Ward
   58641dba0625ab5617f0f76b255eb3142a7935f9,Hettie,Ward
   f335fee4e96916b6cfa436e1d31472420482b870,Marian,Wise
   e828571433842e54e92ad2c8914899b079690d14,Fanny,Baker
   61b1b6752deffffcc37c5012ecdec29221ae50c9,Grace,Thompson
   99668d2e5a1403be3ac9d974fc9cf9921aaaf17f,Jeff,Chapman
   eee74b5ba2e378640c1f1744db6e1e10611b969f,William,Myers
   6586f60a7a40ed8706d9eeb9afdd4bdfbd8cd86f,Darrell,Wilkins
   d0618d5882c0e905653000350b3d7097bf576986,Erik,Dawson
   498ffe5b54315931eb6d7b79c2c4ccf03e2b2f39,Timothy,Little
   277f876145316ce20237bf487ab7424f39c40378,Keith,Guzman
   53f8057cd1f3a8edf3bc50666fe1723b1ab97e66,Lucile,Stokes
   a40203f933f354bfbae63dd6886772b2ae31cacd,Jessie,Wade
   4acb511cfbc625f5744dd216485a2922ffb7057a,Mark,Yates
   f8bb2809aaf3835724bbf193bf37138c32b25270,Eleanor,Munoz
   5419069fe539567f847485e8f4ec3fea3787d04b,Annie,Black
   ec1401eff8eb0df7760cad3984289ab357fc3b2c,Chase,Richards
   d54718af65b2850e0ad35b3003ef01c4153c2b95,Maggie,Higgins
   7feef75ac3c189116e69c5dd28e35ea931c84b8b,Patrick,Mack
   1dd1c77de058fbf25bf736b2445a9bf36c67d88c,Luis,Hughes
   7feef75ac3c189116e69c5dd28e35ea931c84b8b,Patrick,Mack
   58641dba0625ab5617f0f76b255eb3142a7935f9,Hettie,Ward
   999a480139259d9cebeced7798199b9fe2fe3ffe,Anthony,Carlson
   4905443a2d4ceb29a67680f18f53d3cca4c2cd96,Frances,Ross
   58641dba0625ab5617f0f76b255eb3142a7935f9,Hettie,Ward
   2029df4d426b57f47d299314a61df7f1ec2ca574,Leon,Baldwin
   8b3ba5832652b7f434e212721dee7b7ed62a52de,Josephine,Bass
   29b45977bc48fdf4ebb2c8aa71ac3724eb7f8873,Marvin,Bailey
   00d2e06e75391fb0e46d0b90655f40ee83f221a2,Mollie,Reese
   8be1358a2441834b1bd4c48f9c5160c0a562eebc,Jack,Watson
   7feef75ac3c189116e69c5dd28e35ea931c84b8b,Patrick,Mack
   b3d41c0b547f5924e4edb3a69ea6a9223b9363b5,Bradley,Harrison
   58641dba0625ab5617f0f76b255eb3142a7935f9,Hettie,Ward
   78ea1f741b3618af9396c637d28d807e9250d6f9,Thomas,Wallace
   00d2e06e75391fb0e46d0b90655f40ee83f221a2,Mollie,Reese
   90f72e91418d6c1fc618a90aed0aa29236539c17,Max,Medina
   1cfc5e74b072e5e50a1423d6c8761fc127fb9a65,Christopher,More
   69e676e6b0774534eba6967cad95e92a64091631,Harriett,Fitz
   7c81b4077cef9ca5ef0e5184bbaef35d05eaf1c0,Vera,Reese
   7feef75ac3c189116e69c5dd28e35ea931c84b8b,Patrick,Mack
   6ea1ceeb4d32f8bb24ac257ede4b770e7d50e9f3,Jay,Curry
   7feef75ac3c189116e69c5dd28e35ea931c84b8b,Patrick,Mack
   f4e40992f5cd461e33c77cd856156a88d48799db,Mabel,Vasquez
   1af4ea10c66dac8b5e5420f583ae6df0a343fbaf,Wayne,Day
   f4e40992f5cd461e33c77cd856156a88d48799db,Mabel,Vasquez
   056dc39a305fe89371841a0e62e1d1fa05ab2fc1,Seth,Beck
   695128a9604c92f4222a3b1de1cd76765ff26359,Sue,Collier
   00d2e06e75391fb0e46d0b90655f40ee83f221a2,Mollie,Reese
    • Hettie should appear in 7 records
    • Mabel should appear in 4 records
    • Mollie should appear in 6 records
    • Patrick should appear in 8 records

  3. Read and process data from an input file using csv Python package.

  4. Write the data from the input file with 1 new column inserted, using csv Python package.

    • This new column should represent the number of instances of the record immediately to its left

  5. Enable command line inputs using argparse (with auxiliary use of os and sys) for that sweet UX

    • Path to csv input file
    • Column name in question
    • OPTIONAL: Boolean flag that enables descending sort based on first: named column and second: count