23

I'm trying to read the data from .sas7bdat format of SAS using pandas function read_sas:

import pandas as pd
df = pd.read_sas('D:/input/houses.sas7bdat', format = 'sas7bdat')
df.head()

And I have two data types in the df dataframe - float64 and object. I completely satisfied with the float64 datatype, so I can freely convert it to int, string etc. The problem is with object data type, which I can see in the df dataframe wrapped like this:

b'Text'

or like this:

b'12345'

instead of 

Text

or 

12345

I can't convert it to string or int respectively or to "normal" object data type. Also I can't eleminate b'' using slice or replace technics. So I'm not able to use columns with the object data type. Please, tell me how can I get rid of b''.

Joe
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doktr
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    Here you have reference to similar problem in Python: [Convert bytes to a Python string](http://stackoverflow.com/questions/606191/convert-bytes-to-a-python-string). – fl0r3k Aug 13 '16 at 08:43
  • Thanks a lot, this is really helpful! – doktr Aug 13 '16 at 09:31

3 Answers3

27

add this encoding="utf-8"

so the line would be as follows:

df = pd.read_sas('D:/input/houses.sas7bdat', format = 'sas7bdat', encoding="utf-8")
MAFiA303
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21

First, figure out your sas dataset encoding. In SAS, run proc contents on the dataset. Check the "Encoding". In my case, my encoding was "latin1 Western (ISO)". Then enter your encoding as such:

df = pd.read_sas('filename', format = 'sas7bdat', encoding = 'latin-1')
Eric
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3

The encoding argument in pd.read_sas() leads me to have very large dataframes which lead me to have memory related errors.

An other way to deal with the problem would be to convert the byte strings to an other encoding (e.g. utf8).

Example:

Example dataframe:


df = pd.DataFrame({"A": [1, 2, 3], 
                   "B": [b"a", b"b", b"c"], 
                   "C": ["a", "b", "c"]})

Transform byte strings to strings:

for col in df:
    if isinstance(df[col][0], bytes):
        print(col, "will be transformed from bytestring to string")
        df[col] = df[col].str.decode("utf8")  # or any other encoding
print(df)

output:

   A  B  C
0  1  a  a
1  2  b  b
2  3  c  c

Useful links:

  1. Pandas Series.str.decode() page of GeeksforGeeks (where I found my solution)

  2. What is the difference between a string and a byte string?

Adrien Pacifico
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