How can I split my dataframe so that consecutive numbers are each in their own dataframe?

Question

I am new to using the python module pandas dataframes and i might have a silly question. I have a large dataframe that is structured as follows:

index	ConsecutiveNumbers
idx1	1
idx2	2
idx3	3
idx4	4
idx5	1
idx6	2
idx7	3
and so on	and so on

How can i get this single dataframe into a list of multiple dataframes that each look like this:

df1:

index	ConsecutiveNumbers
idx1	1
idx2	2
idx3	3
idx4	4

df2:

index	ConsecutiveNumbers
idx5	1
idx6	2
idx7	3

and so on

The tricky part is that not every number series has the same length so the dataframe itself can not be splitted after every 120th row.

I tried to manually search for the beginning and end of the consecutive numbers series (with a for loop that iterrates rowwise through the dataframe). But that's not really fast and I feel like there has to be a better solution (maybe a slicing approach i am unaware of). Since i am new to using dataframes, i lack of experience in this "more advanced" slicing approaches that search for a start and end of a consecutive series and get the inbetween as a new dataframe.

Answer 1

create dictionary of DataFrames by comapre difference of ConsecutiveNumbers column:

dfs = dict(iter(df.groupby((df['ConsecutiveNumbers'].diff().ne(1).cumsum()))))
print (dfs)
{1:        ConsecutiveNumbers
index                    
idx1                    1
idx2                    2
idx3                    3
idx4                    4, 2:        ConsecutiveNumbers
index                    
idx5                    1
idx6                    2
idx7                    3}

If need loop in dictionary:

for k, df in dfs.items():
    print (df)
       ConsecutiveNumbers
index                    
idx1                    1
idx2                    2
idx3                    3
idx4                    4
       ConsecutiveNumbers
index                    
idx5                    1
idx6                    2
idx7                    3