Posted under » Python Data Analysis on 12 June 2023
From Dataframe intro.
If your data sets are stored in a file, Pandas can load them into a DataFrame.
import pandas as pd df = pd.read_csv('data.csv') print(df) Duration Pulse Maxpulse Calories 0 60 110 130 409.1 1 60 117 145 479.0 2 60 103 135 340.0 .. ... ... ... ... 167 75 120 150 320.4 168 75 125 150 330.4 [169 rows x 4 columns]
Or if there is a first col and you want to index it.
df = pd.read_csv('data.csv', index_col ="stage")
If you want to add new columns to your dataframe.
Big data sets are often stored, or extracted as JSON. From file 'data.json'
import pandas as pd df = pd.read_json('data.json') print(df.to_string())
Load a Python Dictionary into a DataFrame
data = { "Duration":{ "0":60, "1":60, "2":60, "3":45, "4":45, "5":60 }, "Pulse":{ "0":110, "1":117, "2":103, "3":109, "4":117, "5":102 }, "Maxpulse":{ "0":130, "1":145, "2":135, "3":175, "4":148, "5":127 }, "Calories":{ "0":409, "1":479, "2":340, "3":282, "4":406, "5":300 } } df = pd.DataFrame(data) print(df)
cont... Analyzing DataFrames