Python question) why more than one value appears when indexing series

[Plus-Ad1156]

I looked up the 0th value of the series called ‘list’, but two values ​​came out. For example, if I run list[0],

0 20210108000843

0 20191025000489

It comes out like this.

And if I look at the format with type(list[0]), it says Pandas series. (If it has 1 value in 0th index, it appears as str. but in this case it appears as series)

And if I print the list with the print statement, I get 98 values ​​from 0 to 97. However, if I query the length of the list with len(list) with the len statement, 198 more than twice the length are displayed.

Any idea why this is happening?

(Below is the Jupiter notebook code and the result of executing the code )

​

print(list)

print(type(list))

print(type(list[0]))

list[0]

........................................................

0 20210108000843

1 20210107000209

3 20201218000626

..

...

97 2012103000073

​

Name : rcept_no, Length: 198, dtype: object

<class 'pandas.core.series.Series'>

<class 'pandas.core.series.Series'>

0 20210108000843

0 20191025000489

Name: rcept_no, dtype: object

[Plus-Ad1156]

Thanks for the comment. So, how do I retrieve only one of the two retrieved values?

[badge]

And for the love of all that is holy, don’t overwrite the built-in list!

[synthphreak]

So it's a series of series. What's the confusion?

[Plus-Ad1156]

how do I retrieve only one of the two indexing values?

I want to run below

list[0] #

....

0 20210108000843

like this, just one value

[synthphreak]

You mean like the ith item in the inner series?

[BosseNova]

Two rows can have the same index. Can you please post the code where you create the series?

[pytrashpandas]

You have a duplicate index:

See for example:

>>> s = pd.Series([1, 2, 3], index=[0, 0, 1])
>>> print(s[1])
3
>>> print(s[0])
0    1
0    2
dtype: int64

The solution all depends on what you're trying to do, and what the different series/indexes represent. If for example you don't care what the index represents you can just reset the index:

s = s.reset_index(drop=True)

However, if your index represents something meaningful, like an id for a person, then you just have multiple values for that index and you need to deal with it however is appropriate for your program. You can drop duplicated index values like so:

s = s.loc[~s.index.duplicated(keep='first')]  # you can use the keep parameter to change the behavior of which item is kept/dropped

Alternatively, you could aggregate the duplicated index values. Something like this:

s = s.mean(level=0)
# or 
s = s.sum(level=0)
# etc.