pandas.read_csv(): Can't convert 'int' object to str implicitly

Question

When importing my .txt file, I am getting the following error:

Can't convert 'int' object to str implicitly

I import my .txt file as follows:

activityHeaders = ['Type', 'AccountID', 'ConID', 'SecurityID', 'Symbol', 'BBTicker', 'Currency', 'BaseCurrency', 'TradeDate', 'SettleDate', 'TransactionType', 'Quantity', 'UnitPrice', 'GrossAmount', 'SECFee', 'Commission', 'NetInBase', 'FXRatetoBase', 'Other1', 'Other2', 'Description']

dfActivity = pd.read_csv(activityFileUrl, skiprows=[1], header=activityHeaders, error_bad_lines=False)

and my .txt file looks as follows:

"H","I000000","Activity","20100407","16:02:38","20100329","1.0"
"D","I000000","","","","","CAD","EUR","20100329","20100329","WITH","0","0","-14.88","0","0","0","-14.88","-10.8158","",,"CASH TRANSFER (INTERNAL)"
"D","I000000","","","","","AUD","EUR","20100328","20100328","ADJ","0","0","4","0","0","0","4","2.7211","",,"CLIENT FEE (U000001, Commission)"
"D","U000001","37036548","DE000A0F6MD5","PRA","STK","EUR","EUR","20100329","20100331","SELL","-300","7.776","-2332.8","0","-6","0","2326.8","2326.8","405346125","FI","TRADE PRAKTIKER BAU-UND HEIMWERK A"

I don't understand where the int could come from. Note that I skip the first and last row using the skiprows and error_bad_lines. I put header also to None and it returned the same error.

That worked indeed. But now I need to add these columns and it returns that the first line has not been skipped. I.e. it thinks that there are 7 columns and not 21? — WJA
– WJA, Commented Mar 30, 2017 at 11:03

jezrael · Accepted Answer · 2017-03-30 11:13:23Z

You need change header to names if need column names by list activityHeaders.

df = pd.read_csv(StringIO(temp), names=activityHeaders, skiprows=1, error_bad_lines=False)
print (df)
      Type   AccountID         ConID SecurityID Symbol BBTicker Currency  \
D  I000000         NaN           NaN        NaN    NaN      CAD      EUR   
D  I000000         NaN           NaN        NaN    NaN      AUD      EUR   
D  U000001  37036548.0  DE000A0F6MD5        PRA    STK      EUR      EUR   

   BaseCurrency  TradeDate SettleDate                 ...                  \
D      20100329   20100329       WITH                 ...                   
D      20100328   20100328        ADJ                 ...                   
D      20100329   20100331       SELL                 ...                   

   Quantity  UnitPrice  GrossAmount  SECFee  Commission  NetInBase  \
D     0.000     -14.88            0       0           0     -14.88   
D     0.000       4.00            0       0           0       4.00   
D     7.776   -2332.80            0      -6           0    2326.80   

   FXRatetoBase       Other1  Other2                         Description  
D      -10.8158          NaN     NaN            CASH TRANSFER (INTERNAL)  
D        2.7211          NaN     NaN    CLIENT FEE (U000001, Commission)  
D     2326.8000  405346125.0      FI  TRADE PRAKTIKER BAU-UND HEIMWERK A  

[3 rows x 21 columns]

Also if need NOT skip second row omit skiprows:

df = pd.read_csv(StringIO(temp), names=activityHeaders, error_bad_lines=False)
print (df)
  Type AccountID     ConID    SecurityID    Symbol  BBTicker Currency  \
0    H   I000000  Activity      20100407  16:02:38  20100329      1.0   
1    D   I000000       NaN           NaN       NaN       NaN      CAD   
2    D   I000000       NaN           NaN       NaN       NaN      AUD   
3    D   U000001  37036548  DE000A0F6MD5       PRA       STK      EUR   

  BaseCurrency   TradeDate  SettleDate     ...      Quantity  UnitPrice  \
0          NaN         NaN         NaN     ...           NaN        NaN   
1          EUR  20100329.0  20100329.0     ...           0.0      0.000   
2          EUR  20100328.0  20100328.0     ...           0.0      0.000   
3          EUR  20100329.0  20100331.0     ...        -300.0      7.776   

   GrossAmount  SECFee  Commission  NetInBase  FXRatetoBase     Other1  \
0          NaN     NaN         NaN        NaN           NaN        NaN   
1       -14.88     0.0         0.0        0.0        -14.88   -10.8158   
2         4.00     0.0         0.0        0.0          4.00     2.7211   
3     -2332.80     0.0        -6.0        0.0       2326.80  2326.8000   

        Other2  Description  
0          NaN          NaN  
1          NaN          NaN  
2          NaN          NaN  
3  405346125.0           FI  

[4 rows x 21 columns]

elPastor · Accepted Answer · 2017-03-30 11:10:54Z

1

Drop the headers parameter altogether. headers is used as an integer list to tell pandas which row(s) to use as your header.

Change to skiprows=[0] and you should be good.

edited Mar 30, 2017 at 11:10

answered Mar 30, 2017 at 11:05

elPastor

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