pyodide/benchmark/benchmarks/pandas_benchmarks/read_csv.py

11 lines
300 B
Python

# setup: import random ; TESTDATA = "col1;col2;col3\n" + "\n".join(";".join(map(str, [random.randint(0, 1) for _ in range(3)])) + "\n" for _ in range(10000))
# run: read_csv(TESTDATA)
from io import StringIO
import pandas as pd
def read_csv(data):
return pd.read_csv(StringIO(data), sep=";")