Python Pandas "<" operator against "<=" error-CodePudding

I'm targeting to find provisional minimums in a dataframe. To find them I search values that are lower than the minimum of the previous 3 values in a dataframe colum. Tested in Google Colab and python 3.9 in windows.

Maybe there is other more Pandastic way of doing this.

The problem: when using <= everything seems to work fine, but when using <, nothing was found. Even when the provided data should be matched.

import pandas as pd    
data_list = [55,66,77,88,99,88,77,66,55,54,65,67,68,70,73,78,83]  # use any other values
low = pd.Series(data_list)
df = pd.DataFrame(low.values, columns=['Low'])
df
        Low
    0   55
    1   66
    2   77
    3   88
    4   99
    5   88
    6   77
    7   66
    8   55
...

df.plot(grid=True)

When trying to find values lower than the 3 previos rows OR EQUAL, everything works fine:

df[df['Low'] <= df['Low'].rolling(3).min()]

Low
5   88
6   77
7   66
8   55
9   54

The Problem: But when using just < operator, nothing was found.

df[df['Low'] < df['Low'].rolling(3).min()]

This are the versions used in google colab (python 3.7), updated:

!pip install numpy --upgrade
!pip install pandas --upgrade
!pip freeze ...
numpy==1.21.5
pandas==1.3.5

When using local Python 3.9, same behaviour.

CodePudding user response：

trying to find values lower than the 3 previos rows

When you do df[df['Low'] <= df['Low'].rolling(3).min()] or df[df['Low'] < df['Low'].rolling(3).min()] you are not comparing to 3 previous rows but current row and 2 previous.

You need to shift if you want to get desired behavior that is

import pandas as pd    
data_list = [55,66,77,88,99,88,77,66,55,54,65,67,68,70,73,78,83]  # use any other values
low = pd.Series(data_list)
df = pd.DataFrame(low.values, columns=['Low'])
print(df[df['Low'] < df['Low'].rolling(3).min().shift()])

output