Is it possible to find peaks in a csv file and add the peaks in a separate column in the same csv file? (without plotting)
Question:
This is a piece of my code, but I don’t know how to get this array as new column Height to the original csv file in the format?
Date
Level
Height
01-01-2021
45
0
02-01-2021
43
0
03-01-2021
47
1
04-01-2021
46
0
…..
import pandas as pd
from scipy.signal import find_peaks
import matplotlib.pyplot as plt
bestand = pd.read_csv('file.csv', skiprows=1, usecols=[0, 1] , names=['date', 'level'])
bestand = bestand['level']
indices = find_peaks(bestand, height= 37, threshold=None, distance=None)
height = indices[1]['peak_heights']
print(height)
Answers:
I’am not sure I understood your question.
You just want to save the results?
bastand['Heigth'] = indices
bastand.to_csv('file.csv')
I think you want to assign a column named height that takes the value 1 when level is a peak according to find_peaks(). If so:
# Declare column full of zeros
bestand['height'] = 0
# Get row number of observations that are peaks
idx = find_peaks(x=bestand['level'], height=37)[0]
# Select rows in `idx` and replace their `height` with 1
bestand.iloc[idx, 2] = 1
Which returns this:
date level height
0 01-01-2021 45 0
1 02-01-2021 43 0
2 03-01-2021 47 1
3 04-01-2021 46 0
This is a piece of my code, but I don’t know how to get this array as new column Height to the original csv file in the format?
| Date | Level | Height |
|---|---|---|
| 01-01-2021 | 45 | 0 |
| 02-01-2021 | 43 | 0 |
| 03-01-2021 | 47 | 1 |
| 04-01-2021 | 46 | 0 |
| ….. |
import pandas as pd
from scipy.signal import find_peaks
import matplotlib.pyplot as plt
bestand = pd.read_csv('file.csv', skiprows=1, usecols=[0, 1] , names=['date', 'level'])
bestand = bestand['level']
indices = find_peaks(bestand, height= 37, threshold=None, distance=None)
height = indices[1]['peak_heights']
print(height)
I’am not sure I understood your question.
You just want to save the results?
bastand['Heigth'] = indices
bastand.to_csv('file.csv')
I think you want to assign a column named height that takes the value 1 when level is a peak according to find_peaks(). If so:
# Declare column full of zeros
bestand['height'] = 0
# Get row number of observations that are peaks
idx = find_peaks(x=bestand['level'], height=37)[0]
# Select rows in `idx` and replace their `height` with 1
bestand.iloc[idx, 2] = 1
Which returns this:
date level height
0 01-01-2021 45 0
1 02-01-2021 43 0
2 03-01-2021 47 1
3 04-01-2021 46 0