Locate the file
There are two ways to locate the csv file, “absolute path” or “relative path”
e.g.
Absolute path:
“/work/project/data/great.csv
"(Mac) or “C:\work\project\data\great.csv
"(Windows)
Relative path:
“data/greate.csv
"(Mac) or “data\great.csv
"(Windows)
Read with pandas.read_csv()
The result is a dataframe Object
import pandas as pd
import numpy as np
df = pd.read_csv('data/great.csv')
df
company |
locate |
employees |
avenue |
orange |
New York |
10000 |
4000.0 |
banana |
London |
2000 |
1000.0 |
pinch |
Paris |
4000 |
5000.0 |
pear |
Berlin |
3000 |
NaN |
df = pd.read_csv('data/great.csv', header= None)
df
0 |
1 |
2 |
3 |
company |
locate |
employees |
avenue |
orange |
New York |
10000 |
4000 |
banana |
London |
2000 |
1000 |
pinch |
Paris |
4000 |
5000 |
pear |
Berlin |
3000 |
NaN |
Filter rows
df = pd.read_csv('data/great.csv', skiprows=[3,4])
df
company |
locate |
employees |
avenue |
orange |
New York |
10000 |
4000 |
banana |
London |
2000 |
1000 |
lambda is also welcomed
df = pd.read_csv('data/great.csv', skiprows=lambda x:x/2==1)
df
company |
locate |
employees |
avenue |
orange |
New York |
10000 |
4000.0 |
pear |
Berlin |
3000 |
NaN |
Filter columns(or keep wanted)
df = pd.read_csv('data/great.csv', usecols=['company'])
df
company |
orange |
banana |
pinch |
pear |
Other options refer https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html