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

	x	y	dx	dy
0	0	1	0.1	0.2
1	1	2	0.2	0.1
2	2	3	0.3	0.1
3	3	5	0.1	0.4
4	4	5	0.1	0.1
5	5	6	0.1	0.2

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

	x	y	dx	dy	z
0	0	1	0.1	0.2	0
1	1	2	0.2	0.1	2
2	2	3	0.3	0.1	6
3	3	5	0.1	0.4	15
4	4	5	0.1	0.1	20
5	5	6	0.1	0.2	30

data.describe()

	x	y	dx	dy	z
count	6.000000	6.000000	6.000000	6.000000	6.000000
mean	2.500000	3.666667	0.150000	0.183333	12.166667
std	1.870829	1.966384	0.083666	0.116905	11.634718
min	0.000000	1.000000	0.100000	0.100000	0.000000
25%	1.250000	2.250000	0.100000	0.100000	3.000000
50%	2.500000	4.000000	0.100000	0.150000	10.500000
75%	3.750000	5.000000	0.175000	0.200000	18.750000
max	5.000000	6.000000	0.300000	0.400000	30.000000

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

<Axes: xlabel='x'>

To Latex

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

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

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

\begin{tabular}{llll}
\toprule
 & name & mask & weapon \\
\midrule
0 & Raphael & red & sai \\
1 & Donatello & purple & bo staff \\
\bottomrule
\end{tabular}

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

	x	y	z
0	0.00+/-0.10	1.00+/-0.20	0.00+/-0.10
1	1.00+/-0.20	2.00+/-0.10	2.0+/-0.4
2	2.00+/-0.30	3.00+/-0.10	6.0+/-0.9
3	3.00+/-0.10	5.0+/-0.4	15.0+/-1.3
4	4.00+/-0.10	5.00+/-0.10	20.0+/-0.6
5	5.00+/-0.10	6.00+/-0.20	30.0+/-1.2

data.describe()

	x	y	z
count	6	6	6
unique	6	6	6
top	0.00+/-0.10	1.00+/-0.20	0.00+/-0.10
freq	1	1	1

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']))

2.50+/-0.07
2.5+/-1.9

print(data.to_latex())

\begin{tabular}{llll}
\toprule
 & x & y & z \\
\midrule
0 & 0.00+/-0.10 & 1.00+/-0.20 & 0.00+/-0.10 \\
1 & 1.00+/-0.20 & 2.00+/-0.10 & 2.0+/-0.4 \\
2 & 2.00+/-0.30 & 3.00+/-0.10 & 6.0+/-0.9 \\
3 & 3.00+/-0.10 & 5.0+/-0.4 & 15.0+/-1.3 \\
4 & 4.00+/-0.10 & 5.00+/-0.10 & 20.0+/-0.6 \\
5 & 5.00+/-0.10 & 6.00+/-0.20 & 30.0+/-1.2 \\
\bottomrule
\end{tabular}

pandas + plot

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