pandas

see: https://pandas.pydata.org/pandas-docs/stable/

import pandas as pd
from smpl import io

Read

data = pd.read_csv(io.find_file('test_linear_data2.txt',3),delimiter=" ")
data

data['z'] = data['x']*data['y']
data

data.describe()

data.plot(x='x',y='z')

To Latex

df = pd.DataFrame({'name': ['Raphael', 'Donatello'],

                   'mask': ['red', 'purple'],

                   'weapon': ['sai', 'bo staff']})
print(df.to_latex())

Needs

pandas + uncertainties

import uncertainties.unumpy as unp

rdata = pd.read_csv(io.find_file('test_linear_data2.txt',3),delimiter=" ")
data = pd.DataFrame()
data['x'] = unp.uarray(rdata['x'],rdata['dx'])
data['y'] = unp.uarray(rdata['y'],rdata['dy'])
data['z'] = data['x']*data['y']
data

data.describe()

Error once with variance and once without: \(nerr=\sqrt{\text{var}^2+\text{err}^2}\)

from smpl import stat
print(stat.novar_mean(data['x']))
print(stat.mean(data['x']))

print(data.to_latex())

pandas + plot

from smpl import plot
plot.data(data['x'],data['y'])
plot.data(data['x'],data['z'])