Error when merging columns of a pandas dataframe

Question

I have this dataframe:

                 Telefone1   Telefone2
CNPJ                                  
44167450000149  1332385314  1332385314
56095862000108  2125439090  2125439090
59664391000191  1143990005  1143990005

I want to merge "Telefone1" and "Telefone2" into one single column. It should look like this:

                Telefone
CNPJ                                  
44167450000149  1332385314,1332385314
56095862000108  2125439090,2125439090
59664391000191  1143990005,1143990005

For that I'm using this:

df['Telefone']=df.Telefone1.astype(str)+","+df.Telefone2.astype(str)

And I'm getting this traceback:

Traceback (most recent call last):
File "/file.py", line 507, in <module>
'file')
File "file.py", line 347, in function
df['Telefone']=df.Telefone1.astype(str)+","+df.Telefone2.astype(str)
File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/pandas/core/frame.py", line 2357, in __setitem__
self._set_item(key, value)
File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/pandas/core/frame.py", line 2424, in _set_item
NDFrame._set_item(self, key, value)
File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/pandas/core/generic.py", line 1464, in _set_item
self._data.set(key, value)
File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/pandas/core/internals.py", line 3418, in set
self.insert(len(self.items), item, value)
File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/pandas/core/internals.py", line 3519, in insert
placement=slice(loc, loc + 1))
File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/pandas/core/internals.py", line 2518, in make_block
return klass(values, ndim=ndim, fastpath=fastpath, placement=placement)
File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/pandas/core/internals.py", line 1663, in __init__
placement=placement, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/pandas/core/internals.py", line 90, in __init__
len(self.mgr_locs)))
ValueError: Wrong number of items passed 4, placement implies 1

What am I doing wrong here?

You have a typo in your column names. Two columns with name 'Telefone1' but you are trying to add 'Telefone1' and 'Telefone2'. When I corrected for this, your code worked fine. — piRSquared
– piRSquared, Commented Sep 7, 2017 at 23:32
I think you should use .map function instead of astype, please try this code:dataframe["Telefone"] = df["Telefone1"].map(str) + df["Telefone1"] and your column names are telefone1 — Fady Saad
– Fady Saad, Commented Sep 7, 2017 at 23:33
@piRSquared actually I brought that typo up here on stackoverflow. It was a mistake I've made when typing here (already fixed it here). In my code it was correct and it was getting that traceback. — aabujamra
– aabujamra, Commented Sep 8, 2017 at 23:14

Alexander · Accepted Answer · 2017-09-07 23:59:02Z

1

>>> (df.iloc[:, 0].astype(str) + ',' + df.iloc[:, 1].astype(str)).to_frame('Telephone')
                             Telefone
CNPJ                                 
44167450000149  1332385314,1332385314
56095862000108  2125439090,2125439090
59664391000191  1143990005,1143990005

or:

(df.loc[:, 'Telefone1'].astype(str) + ',' + df.loc[:, 'Telefone2'].astype(str)).to_frame('Telefone'))

This works with your sample data. If there is an error, create a new column to indicate the length of each field and sort on this value. There will likely be data errors.

answered Sep 7, 2017 at 23:59

Alexander

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cs95 · Accepted Answer · 2017-09-08 03:45:51Z

df = df.applymap(str)

Option 1

str.cat

df = pd.DataFrame({'Telefone' : df.Telefone1.str.cat(df.Telefone2, sep=',')}, index=df.index)
df
                             Telefone
CNPJ                                 
44167450000149  1332385314,1332385314
56095862000108  2125439090,2125439090
59664391000191  1143990005,1143990005

Option 2

df.apply

df = df.apply(','.join, 1).to_frame(name='Telefone')
df 
                             Telefone
CNPJ                                 
44167450000149  1332385314,1332385314
56095862000108  2125439090,2125439090
59664391000191  1143990005,1143990005

Def_Os · Accepted Answer · 2017-09-08 03:10:03Z

0

Use cat() function of the string accessor:

df = df.astype(str)
df['Telefone'] = df['Telefone1'].str.cat(df['Telefone2'])

edited Sep 8, 2017 at 3:10

answered Sep 7, 2017 at 23:34

Def_Os

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1 Comment

aabujamra Over a year ago

Thanks but this takes me to another error: AttributeError: 'DataFrame' object has no attribute 'str'

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