'Label row when value changes pandas

I need a solution for the following problem. What I have is a timestamp and a value. This value can change positive, negative or remains steady. As soon as it changes positively from one row to another or stays steady, I want to add a label in a new column. If the value continues to increase, the same label should be added to the row. As soon as the value changes negatively, a zero should be entered as label. Can anyone help me?

Input Data

df_raw = pd.DataFrame(
    {
        "timestamp": [
            "2017-06-16 05:19:18.993",
            "2017-06-16 05:19:28.993",
            "2017-06-16 05:19:38.993",
            "2017-06-16 05:19:48.993",
            "2017-06-16 05:19:58.993",
            "2017-06-16 05:25:08.993",
            "2017-06-16 05:25:18.993",
            "2017-06-16 07:44:28.993",
            "2017-06-16 07:45:38.993",
        ],
        "signalvalue": [0.0, 12.0, 22.0, 13.0, 0.0, 30.0, 0.0, 3.0, 6.0],
    }
)

    timestamp                signalvalue
0   2017-06-16 05:19:18.993  0.0
1   2017-06-16 05:19:28.993  12.0
2   2017-06-16 05:19:38.993  22.0
3   2017-06-16 05:19:48.993  13.0
4   2017-06-16 05:19:58.993  0.0
5   2017-06-16 05:25:08.993  30.0
6   2017-06-16 05:25:18.993  0.0
7   2017-06-16 07:44:28.993  3.0
8   2017-06-16 07:45:38.993  6.0

Desired Output

    timestamp                signalvalue    label
0   2017-06-16 05:19:18.993  0.0            0
1   2017-06-16 05:19:28.993  12.0           1
2   2017-06-16 05:19:38.993  22.0           1
3   2017-06-16 05:19:48.993  13.0           0
4   2017-06-16 05:19:58.993  0.0            0
5   2017-06-16 05:25:08.993  30.0           2
6   2017-06-16 05:25:18.993  0.0            0
7   2017-06-16 07:44:28.993  3.0            3
8   2017-06-16 07:45:38.993  6.0            3

Solution 1:^[1]

You can do it with the following function:

def increment_method_1(df,name):
    Results=[]
    last_result=0
    prev_val=0
    for val in df[name].values:
        if val==0 or (val>0 and prev_val>=val):
            Results.append(0)
        elif prev_val<val and prev_val!=0:
            Results.append(last_result)
        elif prev_val<val and prev_val==0:
            last_result+=1
            Results.append(last_result)
        else:
            print(prev_val,val,last_result)
            print("Unexpected condition")
        prev_val=val
    return Results

Solution 2:^[2]

I am assuming you are expecting the output like the following code snippet.

import pandas as pd
import numpy as np

df_raw = pd.DataFrame(
    {
        "timestamp": [
            "2017-06-16 05:19:18.993",
            "2017-06-16 05:19:28.993",
            "2017-06-16 05:19:38.993",
            "2017-06-16 05:19:48.993",
            "2017-06-16 05:19:58.993",
            "2017-06-16 05:25:08.993",
            "2017-06-16 05:25:18.993",
            "2017-06-16 07:44:28.993",
            "2017-06-16 07:45:38.993",
        ],
        "signalvalue": [0.0, 12.0, 22.0, 13.0, 0.0, 30.0, 0.0, 3.0, 6.0],
    }
)

modified = np.zeros((len(df_raw),)).astype(int)
positive = 0 

for i in range(1, len(df_raw)):
    if df_raw["signalvalue"][i] > df_raw["signalvalue"][i - 1]:
        if modified[i - 1] == 0:
            positive += 1
            modified[i] = positive
        else:
            modified[i] = positive

    
df_raw['label'] = modified

Sources

This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.

Source: Stack Overflow

Solution	Source
Solution 1	Hakan Akgün
Solution 2

'Label row when value changes pandas

Solution 1:[1]

Solution 2:[2]

Sources

Related Questions

Solution 1:^[1]

Solution 2:^[2]