Autoincrementing option for Pandas DataFrame index

Question

Is there a way to set an option for auto-incrementing the index of pandas.DataFrame when adding new rows, or to define a function for managing creation of new indices?

Asked By: Gill Bates

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Source

Answer 1

You can set ignore_index=True when append-ing:

In [1]: df = pd.DataFrame([[1,2],[3,4]])

In [2]: row = pd.Series([5,6])

In [3]: df.append(row, ignore_index=True)
Out[3]: 
   0  1
0  1  2
1  3  4
2  5  6

Answered By: Andy Hayden

Answer 2

Note that the accepted answer is dangerous if your existing index is meaningful. For instance:

df = pd.DataFrame(
    [('Alice', 1010, 'sales'), ('Bob', 1011, 'service')],
    columns = ['name', 'emp_id', 'dept']
).set_index('emp_id')

# here's a new employee to append, who has no id:
row = pd.Series({'name': 'Eve', 'dept': 'r&d'})

# this will wipe all the existing employee id numbers:
df.append(row, ignore_index=True)

One way around this would be to manually increment the index:

def add_new_row(df, row):
    row.name = max(df.index)+1
    return df.append(row)

# the existing ids are now preserved:
add_new_row(df, row)

Answered By: alex

Autoincrementing option for Pandas DataFrame index

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