A Pythonic way to read CSV with row and column headers

Question

Let's have a CSV table with row and column headers, e.g.:

, "Car", "Bike", "Boat", "Plane", "Shuttle"
"Red", 1, 7, 3, 0, 0
"Green", 5, 0, 0, 0, 0
"Blue", 1, 1, 4, 0, 1

I want to get row and column headers, i.e.:

col_headers = ["Car", "Bike", "Boat", "Plane", "Shuttle"]
row_headers = ["Red", "Green", "Blue"]
data = [[1, 7, 3, 0, 0],
        [5, 0, 0, 0, 0],
        [1, 1, 4, 0, 1]]

Of course I can do something like

import csv
with open("path/to/file.csv", "r") as f:
    csvraw = list(csv.reader(f))
col_headers = csvraw[1][1:]
row_headers = [row[0] for row in csvraw[1:]]
data = [row[1:] for row in csvraw[1:]]

...but it does not look Pythonic enough.

Is there a neater way for this natural operation?

Answer 1

Take a look at csv.DictReader.

If the fieldnames parameter is omitted, the values in the first row of the csvfile will be used as the fieldnames.

Then you can just do reader.fieldnames. This, of course, only gives you column headers. You would still have to parse the row headers manually.

I think your original solution is pretty good, however.

Answer 2

Now I see that what I want is the easiest (and the most robust) to accomplish with Pandas.

import pandas as pd
df = pd.read_csv('foo.csv', index_col=0)

And if I want, it is easy to extract:

col_headers = list(df.columns)
row_headers = list(df.index)

Otherwise, in the "raw" Python, it seems that the method I wrote in the question is "good enough".