读取具有固定宽度列的 txt 文件

Question

I am trying to open the a dat.txt file from the following website: http://jse.amstat.org/datasets/04cars.dat.txt

And I am not sure which delimiter to use to read it into python as it is separated by spaces.

I tried pd.read_csv('http://jse.amstat.org/datasets/04cars.dat.txt', delimiter = 'sp') along with a several other things but nothing seems to work, as well as:

np.genfromtxt("http://jse.amstat.org/datasets/04cars.dat.txt", delimiter= 'sp')

Note the zeros and ones each represent a separate column.

Answer 1

Use read_fwf instead of read_csv .

[ read_fwf reads] a table of fixed-width formatted lines into DataFrame.
https://pandas.pydata.org/docs/reference/api/pandas.read_fwf.html

import pandas as pd

colspecs = (
    (0, 44),
    (46, 47),
    (48, 49),
    (50, 51),
    (52, 53),
    (54, 55),
    (56, 57),
    (58, 59),
    (60, 66),
    (67, 73),
    (74, 77),
    (78, 80),
    (81, 84),
    (85, 87),
    (88, 90),
    (91, 95),
    (96, 99),
    (100, 103),
    (104, 106),
)

data_url = "http://jse.amstat.org/datasets/04cars.dat.txt"

df = pd.read_fwf(data_url, colspecs=colspecs)

df.columns = (
    "Vehicle Name",
    "Is Sports Car",
    "Is SUV",
    "Is Wagon",
    "Is Minivan",
    "Is Pickup",
    "Is All-Wheel Drive",
    "Is Rear-Wheel Drive",
    "Suggested Retail Price",
    "Dealer Cost",
    "Engine Size (litres)",
    "Number of Cylinders",
    "Horsepower",
    "City Miles Per Gallon",
    "Highway Miles Per Gallon",
    "Weight (pounds)",
    "Wheel Base (inches)",
    "Lenght (inches)",
    "Width (inches)",
)

And the output for print(df) would be:

                        Vehicle Name  ...  Width (inches)
0        Chevrolet Aveo LS 4dr hatch  ...              66
1             Chevrolet Cavalier 2dr  ...              69
2             Chevrolet Cavalier 4dr  ...              68
3          Chevrolet Cavalier LS 2dr  ...              69
4                  Dodge Neon SE 4dr  ...              67
..                               ...  ...             ...
422         Nissan Titan King Cab XE  ...               *
423                      Subaru Baja  ...               *
424                    Toyota Tacoma  ...               *
425     Toyota Tundra Regular Cab V6  ...               *
426  Toyota Tundra Access Cab V6 SR5  ...               *

[427 rows x 19 columns]

Column names and specifications retrieved from here:

• http://jse.amstat.org/datasets/04cars.txt

---

Note: Don't forget to specify where each column starts and ends. Without using colspecs , pandas is making an assumption based on the first row which leads to data errors. Below an extract of a unified diff between generated csv files (with specs and without):