S3Q2 · Column Totals in a Markdown Table¶

⚡ Quick Reference

Type: File-in, stdout-out

Core idea: parse the header, skip the separator, sum each column across all data rows.

import tempfile, sys

_, filename = tempfile.mkstemp(prefix="table_")
with open(filename, "w") as f:
    f.write(sys.stdin.read())

def parse_row(line):
    return [cell.strip() for cell in line.strip().strip("|").split("|")]

with open(filename) as f:
    lines = [l for l in f if l.strip()]

headers = parse_row(lines[0])
# lines[1] is the separator - skip it
data_rows = [parse_row(l) for l in lines[2:]]

totals = [sum(int(row[i]) for row in data_rows) for i in range(len(headers))]

for header, total in zip(headers, totals):
    print(f"{header}: {total}")

Key rules: - Line 1: headers | Line 2: separator (skip) | Lines 3+: data - Parse a row: strip the line, strip outer |, split on |, strip each cell - Sum each column independently across all data rows - Print in column order: header: total

Problem Statement¶

Problem (File I/O → stdout)

Read a markdown table from a file. Compute the sum of each column and print column_name: total for each column in order.

Example:

Input file

| Name | Score | Bonus |
|------|-------|-------|
| A    |    10 |     5 |
| B    |    20 |     3 |
| C    |    15 |     7 |

Output

Name: 0
Score: 45
Bonus: 15

Wait - Name column has non-integer values (A, B, C). The problem says all columns contain integer values. The example above is illustrative; in the actual problem all cell values will be integers.

Corrected example:

Input file

| Month | Revenue | Expenses |
|-------|---------|----------|
|     1 |    1000 |      600 |
|     2 |    1500 |      800 |
|     3 |     900 |      500 |

Output

Month: 6
Revenue: 3400
Expenses: 1900

Parsing a markdown row¶

"| Month | Revenue | Expenses |"

Step 1 - strip()           → "| Month | Revenue | Expenses |"
Step 2 - strip("|")        → " Month | Revenue | Expenses "
Step 3 - split("|")        → [" Month ", " Revenue ", " Expenses "]
Step 4 - strip each cell   → ["Month", "Revenue", "Expenses"]

Solution approaches¶

PythonicExplanatoryUsing zip for column transposition

import tempfile, sys

_, filename = tempfile.mkstemp(prefix="table_")
with open(filename, "w") as f:
    f.write(sys.stdin.read())

def parse_row(line):
    return [cell.strip() for cell in line.strip().strip("|").split("|")]

with open(filename) as f:
    lines = [l for l in f if l.strip()]

headers   = parse_row(lines[0])
data_rows = [parse_row(l) for l in lines[2:]]   # skip separator at index 1

for i, header in enumerate(headers):
    total = sum(int(row[i]) for row in data_rows)
    print(f"{header}: {total}")

import tempfile, sys

_, filename = tempfile.mkstemp(prefix="table_")
with open(filename, "w") as f:
    f.write(sys.stdin.read())

def parse_row(line):
    # Remove surrounding whitespace, strip leading/trailing |, split on |
    cells = line.strip().strip("|").split("|")
    return [cell.strip() for cell in cells]

with open(filename) as f:
    all_lines = [l for l in f.readlines() if l.strip()]

headers   = parse_row(all_lines[0])    # header row
# all_lines[1] is the separator - skip
data_rows = [parse_row(l) for l in all_lines[2:]]

n_cols = len(headers)
totals = [0] * n_cols

for row in data_rows:
    for i in range(n_cols):
        totals[i] += int(row[i])

for header, total in zip(headers, totals):
    print(f"{header}: {total}")

import tempfile, sys

_, filename = tempfile.mkstemp(prefix="table_")
with open(filename, "w") as f:
    f.write(sys.stdin.read())

def parse_row(line):
    return [cell.strip() for cell in line.strip().strip("|").split("|")]

with open(filename) as f:
    lines = [l for l in f if l.strip()]

headers   = parse_row(lines[0])
data_rows = [parse_row(l) for l in lines[2:]]

# Transpose: columns = list of column lists
columns = zip(*data_rows)

for header, col in zip(headers, columns):
    print(f"{header}: {sum(int(v) for v in col)}")

zip(*data_rows) transposes the 2D list - each element of columns is a tuple of all values in that column. sum(int(v) for v in col) totals each column cleanly.

Key takeaways¶

01

Parse row: strip → strip("|") → split("|") → strip each cell

The four-step pipeline handles all whitespace variations: leading/trailing spaces on the line, spaces around the pipes, and spaces inside cells. Works regardless of how the table is formatted.

02

Skip the separator line at index 1

The second line contains |---|---| - not data. Use lines[2:] to skip it. Alternatively, detect separator lines by checking if a line contains only - and | characters.

03

zip(*data_rows) transposes rows to columns

zip(*rows) is the classic Python transpose - converts a list of rows into a list of columns. Paired with zip(headers, columns), it lets you process each column with its header in one clean loop.