AttributeError: 'numpy.ndarray' object has no attribute 'str'

Question

I'm working with pandas for the first time and not sure if what I'm attempting is the best way to accomplish this, but I'm parsing an Excel sheet, trying to make a list of every number in a certain column (column 'C' in my case).

I returned everything from column 'C', removed the empty cells and now I'm trying to remove the '#' character that's in front of the numbers.

Here's my code from before I tried to remove the '#' character, so you can see the output:

def get_prod_cmvp_data():
    prod_cmvp_data = pd.read_excel('_Request ID__Client Cryptographic Module List Template.xlsx', usecols = 'C', header = 6, )
    prod_cmvp = prod_cmvp_data.dropna()
    vals = prod_cmvp.values
    print(vals)

output:

[['#3914']
 [' #3907']
 [' #3197']
 ['#4272']
 ['#4271']
 ['#4254']
 ['#3784']
 ['#3946']
 ['#3888']
 ['#4174']
 ['#4222']
 ['#3613']
 ['#3125']
 ['#3140']
 ['#3197']
 [' #3196']
 [' #3644']
 [' #3615']
 ['#3651']
 ['#3918']
 ['#3946']
 ['#4271']
 ['#3888']
 ['#4174']
 ['#4222']
 ['#3613']
 ['#3125']
 ['#3140']]

Here's my code after I tried to remove the '#' character

def get_prod_cmvp_data():
    prod_cmvp_data = pd.read_excel('_Request ID__Client Cryptographic Module List Template.xlsx', usecols = 'C', header = 6, )
    prod_cmvp = prod_cmvp_data.dropna()
    vals = prod_cmvp.values
    values = vals.str.replace("#", "")
    print(values)

Output:

AttributeError: 'numpy.ndarray' object has no attribute 'str'

Excel File:

Here's a link to the spreadsheet on google sheets, if that's any easier

https://docs.google.com/spreadsheets/d/1yBU4XrfMk54kQorOD7GCQ6kGBYzY_RGf10aHIKy4HLo/edit?usp=sharing

ivanp · Accepted Answer · 2022-09-06 05:58:14Z

1

.values returns a ndarray so won't work with .str.replace.

You should be able to drop

vals = prod_cmvp.values

And use pandas string methods on the pandas series object instead:

prod_cmvp = prod_cmvp_data.dropna()["C"].str.replace("#", "")

Caveats: From what you posted it's not easy to reproduce your input data. The solution above assumes column C holds an array of strings when read with pd. read_excel. Also, it's assumed it's called "C" otherwise replace the string '["C"]' with your correct column name. If you need to see the column names:

prod_cmvp_data.columns

edited Sep 6, 2022 at 5:58

answered Sep 6, 2022 at 4:36

ivanp

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5 Comments

Mitchell Privett Over a year ago

I added the excel file (hopefully I did that correctly) and made the suggested changes and got this error AttributeError: 'DataFrame' object has no attribute 'str'

ivanp Over a year ago

Thanks for the screenshot - I think what would be useful is the actual excel file itself. I've edited the answer to suggest the fix.

Mitchell Privett Over a year ago

When I run "print(prod_cmvp_data.columns)" this is the output: Index(['Unnamed: 2'], dtype='object') when I tried the fix I got a Key Error: 'C'

Mitchell Privett Over a year ago

I'm not sure how to add spreadsheets, but I uploaded it to google docs and added the link

ivanp Over a year ago

The key error means it can't find the column name as mentioned in the text above

Sudhakar · Accepted Answer · 2022-09-06 04:30:49Z

0

please provide excel file, it can done elegantly while reading from file. solution to current problem as below.

col=[['#3914'],
[' #3907'],
[' #3197'],
['#4272'],
['#4271'],
['#4254'],
['#3784'],
['#3946'],
['#3888'],
['#4174'],
['#4222'],
['#3613'],
['#3125'],
['#3140'],
['#3197'],
[' #3196'],
[' #3644'],
[' #3615'],
['#3651'],
['#3918'],
['#3946'],
['#4271'],
['#3888'],
['#4174'],
['#4222'],
['#3613'],
['#3125'],
['#3140']]

for i in col:
    i[0]=i[0].replace('#', '')

answered Sep 6, 2022 at 4:30

Sudhakar

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3 Comments

Mitchell Privett Over a year ago

I just added the excel file, hopefully I did it correctly

Sudhakar Over a year ago

@MitchellPrivett- i can only see snap shot of excel file. better to upload the excel file.

Mitchell Privett Over a year ago

I'm not sure how to add spreadsheets, but I uploaded it to google docs and added the link for that

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