I have a malformed "csv" file:
txt = """NAME;a;b;c
ATTR1;1;2;3
ATTR2;1;2;3;;;
ATTR3;1;2;3;
ATTR4;1;2;3"""
I there a way to use pandas
pd.read_*
toolbox to get the following pd.DataFrame
:
|---+-------+---+---+---|
| | 0 | 1 | 2 | 3 |
|---+-------+---+---+---|
| 0 | NAME | a | b | c |
| 1 | ATTR1 | 1 | 2 | 3 |
| 2 | ATTR2 | 1 | 2 | 3 |
| 3 | ATTR3 | 1 | 2 | 3 |
| 4 | ATTR4 | 1 | 2 | 3 |
|---+-------+---+---+---|
?
PS I know how to do it with import csv
Thank you for ideas and BR, Lex
EDIT
This was a toy example from real file (which I again had to modify) ...
SRC = 'https://dl.dropboxusercontent.com/u/40513206/test.csv'
NA_VALUES = ['', '#N/A N/A', '#N/A Field Not Applicable', '#N/A Invalid Field',
'#N/A Invalid Security', '#N/AN/A', '#N/A Limit', '#####', '#DIV/0!',
'#N/A', '#NAME?', '#NULL!', '#NUM!', '#REF!', '#VALUE!']
CSV_ENCODING = 'WINDOWS-1252'
S_ROWS = 6
NR_ROWS = 60
NR_COLS = 52 # correct nr. of columns, but not always known
dat_m = pd.read_csv(SRC, sep = ';', header = None, index_col = None, skiprows = S_ROWS,
nrows = NR_ROWS, encoding = CSV_ENCODING, na_values = NA_VALUES, names = range(NR_COLS))
Seems that if we use names
parameter then NR_COLS
must be >=
actual nr. of columns in first row, if not so, then Index
or MultiIndex
is formed (based on actual columns), for example if NR_COLS = 50
then index has 2 levels, if NR_COLS = 49
then 3 levels etc.
All this is a result when I save Excel
to csv
, it seems to add sep = ';'
to some rows and for some other reason I can not use xls
(read) files directly.
So I will use large NR_COLS
value or continue with csv
library.
Thank you!
How about:
>>> txt = 'NAME;a;b;c\nATTR1;1;2;3\nATTR2;1;2;3;;;\nATTR3;1;2;3;\nATTR4;1;2;3'
>>> pd.read_csv(StringIO(txt),sep=";",names=range(4))
0 1 2 3
0 NAME a b c
1 ATTR1 1 2 3
2 ATTR2 1 2 3
3 ATTR3 1 2 3
4 ATTR4 1 2 3
[5 rows x 4 columns]
Sometimes when I don't know how many columns there are beforehand I do something silly like names=range(128)
and then .dropna(how='all', axis=1)
.
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