DataParse

DataParse is a tool that can help you in data anaylatics Basic Tasks

CSV Model for training

Installation | Usage | Functions | Concat | DropNa | DropColumn | DropRow | DropDuplicates | ConvertToDateTime | ConvertToInt | ExtractDate | MathMatics | Statics | Operations | Linear | Polynomial | Display | Histogram | Bar | Plot | Scatter

Installation

$ git clone https://github.com/LoaiEsam37/DataParse
$ cd DataParse
$ sudo chmod u+x setup.sh
$ sudo chmod u+x main.py
$ ./setup.sh
$ ./main.py

if you have a problem with running ./main.py try to change the first line in main.py from #!/bin/bash/python3 to #!/bin/bash/python3.10 It depends on what version you have on your pc.

$ cd
$ nano .bashrc

• add this line alias dataparse='python3 Foo/bar/DataParse/main.py' to your .bashrc

• close the terminal and open it again

$ dataparse

Usage

Functions

Concat

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This Function is for concat a directory that full of csv files into a single file

• Here we have a directory that i want to concat to all.csv

• Steps :

DropNa

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This Function is for drop all NaN in csv file

• Steps :

DropColumn

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This Function is for drop the column from csv file that you want

• steps :

DropRow

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This Function is for drop the row from csv file that you want

• Steps :

DropDuplicates

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This Function is for drop duplicates from the Column that you want

• Steps :

ConvertToDateTime

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This Function is to convert Column Values into DateTime

• Steps :

ConvertToInt

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This Function is to convert Column Values into Int

• Steps :

ExtractDate

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This Function is to Extract a Specific kind of date from another Column like: Year, Month, Day, Hour

• In This Example We have Order Date Column and We Want to Extract The Day from it and Put The Values to A new Column named Day:

	Product	Quantity Ordered	Price Each	Order Date	Purchase Address
0	LG Dryer	1	600	2019-03-09 16:34:00	683 12th St, Los Angeles, CA 90001
1	LG Washing Machine	1	600	2019-09-18 17:32:00	925 Forest St, San Francisco, CA 94016
2	Vareebadd Phone	1	400	2019-06-09 14:02:00	853 5th St, Los Angeles, CA 90001
3	20in Monitor	1	109.99	2019-09-18 09:10:00	188 11th St, Austin, TX 73301
4	27in FHD Monitor	1	149.99	2019-09-14 16:06:00	172 Washington St, Los Angeles, CA 90001
5	Flatscreen TV	1	300	2019-09-18 14:54:00	930 North St, Seattle, WA 98101
6	Macbook Pro Laptop	1	1700	2019-09-29 13:37:00	926 North St, San Francisco, CA 94016
7	Wired Headphones	1	11.99	2019-09-18 10:13:00	877 Lincoln St, Boston, MA 02215
8	27in 4K Gaming Monitor	1	389.99	2019-09-24 22:16:00	501 Adams St, Seattle, WA 98101

• steps :

• Result :

	Product	Quantity Ordered	Price Each	Order Date	Purchase Address	Day
0	LG Dryer	1	600	2019-03-09 16:34:00	683 12th St, Los Angeles, CA 90001	9
1	LG Washing Machine	1	600	2019-09-18 17:32:00	925 Forest St, San Francisco, CA 94016	18
2	Vareebadd Phone	1	400	2019-06-09 14:02:00	853 5th St, Los Angeles, CA 90001	9
3	20in Monitor	1	109.99	2019-09-18 09:10:00	188 11th St, Austin, TX 73301	18
4	27in FHD Monitor	1	149.99	2019-09-14 16:06:00	172 Washington St, Los Angeles, CA 90001	14
5	Flatscreen TV	1	300	2019-09-18 14:54:00	930 North St, Seattle, WA 98101	18
6	Macbook Pro Laptop	1	1700	2019-09-29 13:37:00	926 North St, San Francisco, CA 94016	29
7	Wired Headphones	1	11.99	2019-09-18 10:13:00	877 Lincoln St, Boston, MA 02215	18
8	27in 4K Gaming Monitor	1	389.99	2019-09-24 22:16:00	501 Adams St, Seattle, WA 98101	24

MathMatics

Statics

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This Function is to get the mean, mode, median, standard deviation, variance, min, max

• Steps :

• Result :

Operations

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This Function is to Sum, Subtract, Divide, Multiply Two Columns and put the value in a new Column

• In This Example we need to Multiply Quantity Ordered with Price Each and put the values in a new Column named Sales

	Product	Quantity Ordered	Price Each	Order Date	Purchase Address
0	Product	nan	nan	nan	Purchase Address
1	AAA Batteries (4-pack)	3	2.99	2019-09-17 20:56:00	840 Highland St, Los Angeles, CA 90001
2	USB-C Charging Cable	1	11.95	2019-09-30 00:18:00	250 Meadow St, San Francisco, CA 94016

• Steps :

• Result :

	Product	Quantity Ordered	Price Each	Order Date	Purchase Address	Sales
0	Product	nan	nan	nan	Purchase Address	nan
1	AAA Batteries (4-pack)	3	2.99	2019-09-17 20:56:00	840 Highland St, Los Angeles, CA 90001	8.97
2	USB-C Charging Cable	1	11.95	2019-09-30 00:18:00	250 Meadow St, San Francisco, CA 94016	11.95

Linear

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This Function is to Do Linear Equation

• Steps :

• Next step to Show the Data on Matplotlib

Polynomial

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This Function is to do Polynomial Equation

• Steps :

• Next step to Show the Data on Matplotlib

Display

Histogram

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Bar

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Plot

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• CSV :

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• JSON :

  • Linear :

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  • Other :

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Scatter

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