python - Going through a DataFrame using .iloc

Question

What I want to do is save part of the dataframe into a list. I have my DataFrame data_S and when it is printed it looks like this:

data_S

       open     high       low   close      volume      datetime
0    329.30  334.860  327.8800  333.74   5357973.0  1.578290e+12
1    334.26  344.190  330.7100  337.28   9942277.0  1.578377e+12
2    332.40  334.030  329.6000  331.37   8246250.0  1.578463e+12
3    334.95  341.730  332.0500  336.34   8183707.0  1.578550e+12
4    335.56  337.700  329.4548  329.92   7170124.0  1.578636e+12
..      ...      ...       ...     ...         ...           ...
249  216.36  218.554  214.3650  216.67  10812617.0  1.609308e+12
250  216.24  216.900  212.7000  214.06  10487567.0  1.609394e+12
251  210.00  210.200  202.4911  202.72  21225594.0  1.609740e+12
252  204.74  213.350  204.6000  211.63  19338304.0  1.609826e+12
253  210.22  215.610  209.3400  211.03  16202157.0  1.609913e+12

I want to be able to replicate the code below and change the value of the bolded with a for loop value of nums.

list_of_five_day_range = []
#so then it starts with the first list being the most recent and then in
#[X,Y,Z] Z is the most recent high or is in data_S[253]['high']
list_of_max_value = []
bars = data_S.iloc[-**5**:]['high']
list_of_five_day_range.append(list(bars))
max_value = bars.max()
list_of_max_value.append(max_value)    

bars1 = data_S.iloc[**-6:-1**]['high']
list_of_five_day_range.append(list(bars1))
max_value1 = bars1.max()
list_of_max_value.append(max_value1)

max_id = bars.max()

# [X,Y,Z] Z is the most recent with the list at [0] is the most recent data
print(str(list_of_five_day_range) + " this is last 5 days of data")

# with the first number in the list is for the most recent first day high.
print(str(list_of_max_value)+" this is maxium number in last 5 days")

returns

[[218.554, 216.9, 210.2, 213.35, 215.61], [221.68, 218.554, 216.9, 210.2, 213.35]] this is last 5 days of data
[218.554, 221.68] this is maxium number in last 5 days

but in a function and for it to go through the DataFrame. This is what I have so far

def five_day_range(price_history):

    for nums in range(len(price_history.index) - 1):
        list_of_five_day_range = []
        #so then it starts with the first list being the most recent and then [X,Y,Z] Z is the most recent
        list_of_max_value = []
        bars = price_history.iloc[-5 + int(-nums): int(-nums)]["high"]
        list_of_five_day_range.append(bars)
        max_value = bars.max()
        list_of_max_value.append(max_value)
        # print( str(bars)+ " this is the veyr first list of range ")


    return list_of_five_day_range, list_of_max_value

However, when I print(five_day_range(data_S)) this is what I get

([0    334.86
1    344.19
Name: high, dtype: float64], [344.19])

I dont understand why it is printing this when the nums value should be going up the DataFrame. This is how I thought the for loop would go through the DataFrame. enter image description here

I thought it would first append the yellow data then the blue and green, and so on until it hits index[0]/

Answer 1

To answer your first question:

I believe data_S.drop(columns=['high', 'low']) returns another dataframe, which by default requires you to reassign the result into another variable.

With that in mind, you can either do:

data_S = data_S.drop(columns=["high", "low"])

or

data_S.drop(columns=["high", "low"], inplace=True)

UPDATED based on updated question:

Try this, and your list should be returned as expected. You are defining list_of_five_day_range and list_of_max_value as [] on every iteration of the loop. Hope that makes sense.

def five_day_range(price_history):
    list_of_five_day_range = []
    list_of_max_value = []
    for nums in range(len(price_history.index) - 1):
        bars = price_history.iloc[-5 + int(-nums): int(-nums)]["high"]
        list_of_five_day_range.append(bars)
        max_value = bars.max()
        list_of_max_value.append(max_value)

    return list_of_five_day_range, list_of_max_value