I have the following sample .csv file:
str_header int_header
string_a 1
string_b 2
string_c 3
According to solutions on the internet, this code:
import pandas as pd
data = pd.read_csv("z.csv", names=['int_header'])
print(data['int_header'])
should only read int_header column into data. But data, when printed as above, actually contains all of the file columns. I'm using Anaconda distribution of Python. What's wrong?
try this instead:
data = pd.read_csv("z.csv", usecols=['int_header'])
assuming that your CSV file has , as a delimiter
Explanation:
names : array-like, default None
List of column names to use. If file contains no header row, then you should explicitly pass header=None
usecols : array-like, default None
Return a subset of the columns. Results > in much faster parsing time and lower memory usage.
documentation is a bit confusing.
names - used for naming (giving columns names), especially if you don't have a header line or want to ignore/skip it.
usecols - used for choosing only "interesting" columns
