How to edit data in CSV with equations to convert to new values?-CodePudding

I've been trying to find a solution. But most of all, I found only a few lines of csv editing. But the data that I have and have to solve consists of thousands of lines.

The data that I use is the value from the sensor-read. but it comes out in voltage. I need to convert it by using equations (which I already have).But I don't know how to use it to edit with many row in csv.

Data sample

ID	Voltage
1	1979
2	1978
...	...
49999	1976
50000	1976

I want to create new column and convert value from old existing column to new column and export to new csv file. Is there any way that can solve it?

I don't know if I should give an example of the equation. But let's just put it together. My equations will be like

Moisture = 100 - ( 0.01 x Voltage )

Here is sample of csv that I want.

ID	Voltage	Moisture
1	1979	80
2	1978	80
...	...	...
49999	1976	81
50000	1976	81

CodePudding user response：

load the csv into a dataframe, this is done easily with pandas

import pandas as pd

df = pd.read_csv('file_path.csv')

then you can create a new column and assign it a value base of existing columns

df['Moisture'] = 100 - (df['Voltage'] * 0.01)

then you can save the dataframe back to a csv

df.to_csv('file_path.csv', index=False)

CodePudding user response：

You can use csv module for that. You can read data from csv into dictionaries and then just update those dictionaries and write it back. Something like this:

import csv

old_data = list()
with open('data.csv', newline='') as f:
    old_data = list(csv.DictReader(f))
    for d in csv_reader:
        d['Moisture'] = ''

with open('new_data.csv', mode='w') as csv_file:
    writer = csv.DictWriter(csv_file,
                                    fieldnames=['ID', 'Voltage', 'Moisture'],
                                    lineterminator='\n')
            writer.writeheader()
            writer.writerows(old_data)

CodePudding user response：

Did you have a look at the pandas library ? It allows you to manipulate any kind of data.

Here is an example for your case:

import pandas as pd

# Reading your csv file:
df = pd.read_csv("your_csv_file.csv", index="ID")

# Creating a new column:
df["Moisture"] = 100 - (0.01 * df["Voltage"])

# Exporting new csv:
df.to_csv("new_csv_with_moisture.csv")