Here is how to load time series information from CSV file using Pandas.
Assume that the data.csv
file contains date, name, age and weight as follows:
2005-11-01 John 33 100.56 2005-11-02 Nikki 29 77.84
Here is the code to load the data.csv
:
#!/usr/bin/python3 # Reference: https://stackoverflow.com/a/37453925 # https://stackoverflow.com/a/17468012 # http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html import pandas as pd my_headers = ['date', 'name', 'age', 'weight'] my_dtypes = {'date': 'str', 'name': 'str', 'age': 'int', 'weight': 'float'} my_parse_dates = ['date'] loaded_data = pd.read_csv('data.csv', sep=' ', header=None, names=my_headers, dtype=my_dtypes, parse_dates=my_parse_dates) print(loaded_data['date']) print(loaded_data['name']) print(loaded_data['age']) print(loaded_data['weight'])