I have a column in my dataframe being the customer ids which contains no repetitions. The id series starts at integer 1, and ends at 4003. As the following output shows, there are 4 id numbers being skipped. I would like some help in finding out what they are. Thanks in advance!
df['customer_id'].describe()
Out[150]:
count 3999
unique 3999
top 4003
freq 1
Name: customer_id, dtype: int64
Take below dataframe for example:
In [2454]: df
Out[2454]:
customer_id
0 1
1 2
2 3
3 4
4 5
5 8
6 9
7 10
You can use set symmetric difference:
In [2437]: a = df['customer_id'].tolist()
In [2431]: b = [x for x in range(a[0], a[-1] + 1)]
In [2438]: missing_vals = list(set(a) ^ set(b))
In [2439]: missing_vals
Out[2439]: [6, 7]
Assuming the dtype is int (which appears to be the case), it looks like we can use setdiff1d here from numpy:
c_id = df['customer_id']
missing_ids = np.setdiff1d(np.arange(c_id.min(), c_id.max()+1), c_id)