"# Data-organization"
In this File I used Python and Google collab to seperate CSV formatted Data Open This file In google collab and you should be able to Run the code in blocks so you can see every step of the way
Make sure that you uploaded your data into google collabe if you are going to use Google collab, if you are using Other coding software Make sure that your data is in the correct Directory, and That is it in CSV format As this code Is designed for CSV
First Step is to import the necessary Modules
import pandas as pd
import numpy as npNext step is to make sure that your data is the right directory, for use.
After That Use the Pandas Libraries to read in the CSV file as a DataFrame object:
df = pd.read_csv('/content/1m-PDDS(2023-04-12).csv')
Then Sort the Data Frames Based on the Variables
df = df.sort_values(by=['Location', 'Site', 'Plot','Subplot'])
You Can use the print function to view your how your data is organized thus far
print(df_sorted)
print(df_sorted.head())
Should look somthing Like this (Based on the variables you used)
Great! Now We will begin grouping the data
grouped_df.size()
It will look like this showing you how it is grouped and how many times it repeats
Next is Grouping and Download in groups of "Location, Site, Plot" Variables
grouped = df_sorted.groupby(['Location', 'Site', 'Plot'])
for name, group in grouped:
filename = f"{name[0]}_{name[1]}_{name[2]}.csv"
group.to_csv(filename, index=False)
Review Your Data to Make sure all went Well #Happy Coding!