How can I find the missing index using python pandas?

Question

Example

Order_ID Name
1        Man
2        Boss
5        Don
7        Lil
9        Dom
10       Bob

Want to get an output as:

3 4 6 8 are the missing Order_ID

U13-Forward · Accepted Answer · 2021-01-11 10:39:03Z

2

Try using a list comprehension with range:

print([i for i in range(1, 10) if i not in df['Order_ID']])

Output:

[3, 4, 6, 8]

answered Jan 11, 2021 at 10:39

U13-Forward

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Comments

jezrael · Accepted Answer · 2021-01-11 10:38:46Z

1

Solution for generate missing values from index dynamically by maximum and minimum values:

print (np.setdiff1d(np.arange(df.index.min(), df.index.max() + 1), df.index).tolist())
[3, 4, 6, 8]

answered Jan 11, 2021 at 10:38

jezrael

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Hamza usman ghani · Accepted Answer · 2021-01-11 10:42:48Z

0

Convert the list to set and compute its difference with a set that contains integers ranging from min(lst) and max(lst).

lst=df["Order_ID"].to_list()
sorted(set(range(lst[0], lst[-1])) - set(lst))

> [3, 4, 6, 8]

answered Jan 11, 2021 at 10:42

Hamza usman ghani

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Ahmed · Accepted Answer · 2021-01-11 11:45:57Z

0

Try this code;

Code Syntax

missData = list(filter(lambda x: x not in df['Order_ID'],  range(1, df['Order_ID].max()+1)))

print(f"{missData} are the missing Order_ID")

Output

[3, 4, 6, 8] are the missing Order_ID

[Program finished]

answered Jan 11, 2021 at 11:45

Ahmed

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