Creating paired nested list from a list in a column of pandas dataframe where the end element of first pair should be the start element of next

Question

I have a data in geodataframe as shown in the image. It contains a column by name neighbourhood_list which contains the list of all the neighbourhood codes of a route. what i want is to create a nested list in which the end element of first pair should be the start element of next because I want to generate a OD directed network (for generating edges) and order also matters here.

to make it bit clear, here is some code.

Here is lets say one record from the dataframe on which i tried some bodge way to get the desired result

list= [15,30,9,7,8]
new_list=[]
for i in range(len(list)-1):
    new_list.append(list[i])
    new_list.append(list[i+1])

so the above code gives the combined list which i then broke into the pairs which i needed

chunks = [new_list[x:x+2] for x in range(0, len(new_list), 2)]
chunks

Actual data is [15,30,9,7,8] and desired output is [[15, 30], [30, 9], [9, 7], [7, 8]]

I just figured out the above code from the answer here Split a python list into other "sublists" i.e smaller lists

However now the real issue is how to apply it in pandas

so far i am trying to tweak around something mentioned here https://chrisalbon.com/python/data_wrangling/pandas_list_comprehension/

here is some incomplete code, i am not sure if it is correct but i thought if somehow i could get the len of list items from each row of the neighbourhood_list column then maybe i could accomplish

for row in df['neighbourhood_list']:
    for i in range ??HOW TO GET range(len) of each row??
    new.append(row[i])
    new.append(row[i+1])

note: as a layman i dont know how the nested looping or lambda functions work or if there is any available pandas functions to perform this task. another thing i think is of something like this also mentioned on stackoverflow, but still how to get length of list of each row, even if i try to create a function first and then apply it to my column.

df[["YourColumns"]].apply(someFunction)

apologies ahead if the question need more clarification (i can give more details of the problem if needed)

Thanks so much.

Answer 1

My best guess is that you are trying to create a column containing a list of ordered pairs from a column of lists. If that is the case, something like this should work:

Edit

From what you described, your 'neighbourhood_list' column is not a list yet, but is a string. Add this line to turn the column items to lists, then run the pairs apply.

df['neighbourhood_list']=df['neighbourhood_list'].apply(lambda row: row.split(','))
df['pairs'] = df['neighbourhood_list'].apply(lambda row: [[row[i],row[i+1]] for i in range(len(row)-1)])

If I have misunderstood, please let me know and I'll try and adjust accordingly.

Answer 2

From the description you posted, it seems that all you're trying to do is get that list of graph edges from an ordered list of nodes. First, it helps to use existing methods to reduce your pairing to a simple expression. In this case, I recommend zip:

stops = [15,30,9,7,8]
list(zip(stops, stops[1:]))

Output:

[(15, 30), (30, 9), (9, 7), (7, 8)]

Note that I changed your variable name: using a built-in type as a variable name is a baaaaaad idea. It disables some of your ability to reference that type.

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Now, you just need to wrap that in a simple column expression. In any PANDAS tutorial, you will find appropriate instructions on using df["neighourhood_list"] as a series expression.