检查熊猫数据框中的重复序列

Question

I have a pandas Dataframe, a column of which has a repeating sequence of values which almost looks like the following:

      Cell
0      x_a
1      x_b
2      x_c
3      x_a
4      x_b
5      x_c
6      x_a
7      x_b
8      x_b
9      x_c
10     x_c
11     x_b
12     x_a

I need to check through this entire column to see that the repetition of this sequence "x_a, x_b, x_c" is exactly maintained in this order, ie "x_c" follows x_b" follows "x_a".

Wherever this order is broken, eg in indices 7 and 8 where "B" is repeated twice or 10, 11, 12 where the order is wrong, I need to be able to find out which value is playing foul?

Any pointers on how to do it?

I've been scratching my head with df.loc all this while but to no avail and I'm fairly certain df.loc is not the right way.

Thanks in advance guys.

Answer 1

I wrote this solution with a pre-defined rule for the order:

import pandas as pd

#Creating Dummy Dataframe
dummy_frame = pd.DataFrame(columns=["dummy"])

#Adding Dummy Values to the DataFrame
dummy_frame["dummy"] = ["x_a","x_b","x_c","x_a","x_b","x_c","x_a","x_a","x_b"]

#Pre-defining order to check in the dataframe
correct_order = ["x_a","x_b","x_c"]

#For Loop Based on length of the order (Triplets in this case)
for i in range(0,len(dummy_frame),len(correct_order)):

    #Check if the order is matched
    if correct_order != dummy_frame["dummy"][i:i+3].tolist():
        for j in range(len(correct_order)):

            #Check for the incorrect value in the triplet
            if correct_order[j] != dummy_frame["dummy"][i:i+3].tolist()[j]:
                print "Value at index:",i+j,"is incorrect."
                print "Current Value:",dummy_frame["dummy"][i:i+3].tolist()[j],"Correct Value is:",correct_order[j]

Sample Output:

Value at index: 7 is incorrect.
Current Value: x_a Correct Value is: x_b
Value at index: 8 is incorrect.
Current Value: x_b Correct Value is: x_c

Hope this helps :)