Can pandas handle variable-length whitespace as column delimiters

pandas, python

Solution

I think there's just a missing `\` in the docs (maybe because it was interpreted as an escape marker at some point?) It's a regexp, after all:

In [68]: data = read_table('sample.txt', skiprows=3, header=None, sep=r"\s*")

In [69]: data
Out[69]: 
<class 'pandas.core.frame.DataFrame'>
Int64Index: 7 entries, 0 to 6
Data columns:
X.1     7  non-null values
X.2     7  non-null values
X.3     7  non-null values
X.4     7  non-null values
X.5     7  non-null values
X.6     7  non-null values
[...]
X.23    7  non-null values
X.24    7  non-null values
X.25    5  non-null values
X.26    3  non-null values
dtypes: float64(8), int64(10), object(8)

Because of the delimiter problem noted by @MRAB, it has some trouble with the last few columns:

In [73]: data.ix[:,20:]
Out[73]: 
   X.21  X.22           X.23                   X.24            X.25    X.26
0   315  0.95            ABC            transporter   transmembrane  region
1   527  0.93            ABC            transporter            None    None
2   408  0.86  RecF/RecN/SMC                      N        terminal  domain
3   575  0.85  RecF/RecN/SMC                      N        terminal  domain
4   556  0.72            AAA                 ATPase          domain    None
5   275  0.85      YceG-like                 family            None    None
6   200  0.85       Pyridine  nucleotide-disulphide  oxidoreductase    None

but that can be patched up at the end.

Problem

I have a textfile where columns are separated by variable amounts of whitespace. Is it possible to load this file directly as a pandas dataframe without pre-processing the file? In the pandas documentation the delimiter section says that I can use a `'s*'` construct but I couldn't get this to work. ``` ## sample data head sample.txt # --- full sequence --- -------------- this domain ------------- hmm coord ali coord env coord # target name accession tlen query name accession qlen E-value score bias # of c-Evalue i-Evalue score bias from to from to from to acc description of target #------------------- ---------- ----- -------------------- ---------- ----- --------- ------ ----- --- --- --------- --------- ------ ----- ----- ----- ----- ----- ----- ----- ---- --------------------- ABC_membrane PF00664.18 275 AAF67494.2_AF170880 - 615 8e-29 100.7 11.4 1 1 3e-32 1e-28 100.4 7.9 3 273 42 313 40 315 0.95 ABC transporter transmembrane region ABC_tran PF00005.22 118 AAF67494.2_AF170880 - 615 2.6e-20 72.8 0.0 1 1 1.9e-23 6.4e-20 71.5 0.0 1 118 402 527 402 527 0.93 ABC transporter SMC_N PF02463.14 220 AAF67494.2_AF170880 - 615 3.8e-08 32.7 0.2 1 2 0.0036 12 4.9 0.0 27 40 391 404 383 408 0.86 RecF/RecN/SMC N terminal domain SMC_N PF02463.14 220 AAF67494.2_AF170880 - 615 3.8e-08 32.7 0.2 2 2 1.8e-09 6.1e-06 25.4 0.0 116 210 461 568 428 575 0.85 RecF/RecN/SMC N terminal domain AAA_16 PF13191.1 166 AAF67494.2_AF170880 - 615 3.1e-06 27.5 0.3 1 1 2e-09 7e-06 26.4 0.2 20 158 386 544 376 556 0.72 AAA ATPase domain YceG PF02618.11 297 AAF67495.1_AF170880 - 284 3.4e-64 216.6 0.0 1 1 2.9e-68 4e-64 216.3 0.0 68 296 53 274 29 275 0.85 YceG-like family Pyr_redox_3 PF13738.1 203 AAF67496.2_AF170880 - 352 2.9e-28 99.1 0.0 1 2 2.8e-30 4.8e-27 95.2 0.0 1 201 4 198 4 200 0.85 Pyridine nucleotide-disulphide oxidoreductase #load data from pandas import * data = read_table('sample.txt', skiprows=3, header=None, sep=" ") ValueError: Expecting 83 columns, got 91 in row 4 #load data part 2 data = read_table('sample.txt', skiprows=3, header=None, sep="'s*' ") #this mushes some of the columns into the first column and drops the rest. X.1 1 ABC_tran PF00005.22 118 AAF67494.2_ 2 SMC_N PF02463.14 220 AAF67494.2_ 3 SMC_N PF02463.14 220 AAF67494.2_ 4 AAA_16 PF13191.1 166 AAF67494.2_ 5 YceG PF02618.11 297 AAF67495.1_ 6 Pyr_redox_3 PF13738.1 203 AAF67496.2_ 7 Pyr_redox_3 PF13738.1 203 AAF67496.2_ 8 FMO-like PF00743.14 532 AAF67496.2_ 9 FMO-like PF00743.14 532 AAF67496.2_ ``` While I can preprocess the files to change the whitespace to commas/tabs it would be nice to load them directly. (FYI this is the *.hmmdomtblout output from the hmmscan program)

Original source

Related problems