I'm trying to mix StringIO and BytesIO with pandas and struggling with some basic stuff. For example, I can't get "output" below to work, whereas "output2" below does work. But "output" is closer to the real world example I'm trying to do. The way in "output2" is from an old pandas example but not really a useful way for me to do it.
import io # note for python 3 only # in python2 need to import StringIO output = io.StringIO() output.write('x,y\n') output.write('1,2\n') output2 = io.StringIO("""x,y 1,2 """)
They seem to be the same in terms of type and contents:
type(output) == type(output2) Out[159]: True output.getvalue() == output2.getvalue() Out[160]: True
But no, not the same:
output == output2 Out[161]: False
More to the point of the problem I'm trying to solve:
pd.read_csv(output) # ValueError: No columns to parse from file pd.read_csv(output2) # works fine, same as reading from a file
The difference between read_csv() and read_table() is almost nothing. In fact, the same function is called by the source: read_csv() delimiter is a comma character. read_table() is a delimiter of tab \t .
The pandas. read_csv is used to load a CSV file as a pandas dataframe. In this article, you will learn the different features of the read_csv function of pandas apart from loading the CSV file and the parameters which can be customized to get better output from the read_csv function.
We can read data from a text file using read_table() in pandas. This function reads a general delimited file to a DataFrame object. This function is essentially the same as the read_csv() function but with the delimiter = '\t', instead of a comma by default.
io.StringIO
here is behaving just like a file -- you wrote to it, and now the file pointer is pointing at the end. When you try to read from it after that, there's nothing after the point you wrote, so: no columns to parse.
Instead, just like you would with an ordinary file, seek
to the start, and then read:
>>> output = io.StringIO() >>> output.write('x,y\n') 4 >>> output.write('1,2\n') 4 >>> output.seek(0) 0 >>> pd.read_csv(output) x y 0 1 2
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