Removing square brackets in pandas python export of numpy array to excel

Question

Using the following function:

def exportExcel(data):
    df = pd.DataFrame(data)
    filepath = 'Output.xlsx'
    df.to_excel(filepath, index=False)

Output after exporting the np.array to excel columns

    column a       column b     column c
    [[0.00536237] [0.00536237]] [0.01030928]
    [[0.00652899] [0.00652899]] [0.]
    [[0.00579218] [0.00579218]] [0.]

How can I remove all the squared brackets?

I have tried several solutions, but they don´t work:

for col in df:
df[col] = df[col].str.extract(r'\[(.*)\]')

Thank you

What do you see for type(df['column a'].iloc[0]) ? It's important to know whether you have strings, a list, an array, or something else. — jpp
– jpp, Commented Aug 7, 2018 at 11:33
AttributeError: Can only use .str accessor with string values, which use np.object_ dtype in pandas — Manuel Almeida
– Manuel Almeida, Commented Aug 7, 2018 at 11:42

Sreekiran A R · Accepted Answer · 2018-08-07 12:03:36Z

3

If the column is in numpy, you can make use of the function np.squeeze()

df[col]=np.squeeze(df[col].tolist())

answered Aug 7, 2018 at 12:03

Sreekiran A R

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Comments

Joe · Accepted Answer · 2018-08-07 11:39:58Z

2

If they are string, you can use replace:

df[col] = df[col].str.replace('[','')
df[col] = df[col].str.replace(']','')

Or if the square brackets you want to remove are only at the start or end of the string, with strip:

df[col] = df[col].str.strip('[')
df[col] = df[col].str.strip(']')

edited Aug 7, 2018 at 11:39

answered Aug 7, 2018 at 11:34

Joe

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6 Comments

Manuel Almeida Over a year ago

I see this: AttributeError: Can only use .str accessor with string values, which use np.object_ dtype in pandas

Joe Over a year ago

What type are the columns? see jpp comment

Manuel Almeida Over a year ago

I can´t see the type

Manuel Almeida Over a year ago

they are the square brackets of a numpy array

Manuel Almeida Over a year ago

TypeError: unhashable type: 'numpy.ndarray'

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