How set display precision for a DataFrame?

[swol...@gmail.com]

Hello,

I'm starting with Julia and wanted to use DataFrames in homeworks to present the data, but I've stumbled upon a problem.

When running the below code you'll see three lists of Float64 values.

Problem is when I'm showing the DataFrame I'm loosing lots of information, because of the display precision.

Is there a way to change it? In Pandas I would do Pandas.set_option('display.precision', 20).

xlist = [(1/8)^i for i=1:20]

fx = map(x -> sqrt(x^2 + 1) -1, xlist)

gx = map(x -> x^2/(sqrt(x^2 + 1)+1), xlist)

println("|x                 | f(x)              | g(x)              |")

for i=1:20

  # @printf("|%1.60f | %1.60f | %1.60f |\n", xlist[i], fx[i], gx[i])

  println("$(xlist[i]) \t\t| $(fx[i]) \t\t| $(gx[i])")

end

using DataFrames

df = DataFrame(x = xlist, f_x = fx, g_x = gx)

# rename!(df, ["b", "c"], ["f(x)", "g(x)"])

showall(df)

println("\n")

|x                 | f(x)              | g(x)              |
0.125 		| 0.0077822185373186414 		| 0.0077822185373187065
0.015625 		| 0.00012206286282867573 		| 0.00012206286282875901
0.001953125 		| 1.9073468138230965e-6 		| 1.907346813826566e-6
0.000244140625 		| 2.9802321943606103e-8 		| 2.9802321943606116e-8
3.0517578125e-5 		| 4.656612873077393e-10 		| 4.6566128719931904e-10
3.814697265625e-6 		| 7.275957614183426e-12 		| 7.275957614156956e-12
4.76837158203125e-7 		| 1.1368683772161603e-13 		| 1.1368683772160957e-13
5.960464477539063e-8 		| 1.7763568394002505e-15 		| 1.7763568394002489e-15
7.450580596923828e-9 		| 0.0 		| 2.7755575615628914e-17
9.313225746154785e-10 		| 0.0 		| 4.336808689942018e-19
1.1641532182693481e-10 		| 0.0 		| 6.776263578034403e-21
1.4551915228366852e-11 		| 0.0 		| 1.0587911840678754e-22
1.8189894035458565e-12 		| 0.0 		| 1.6543612251060553e-24
2.2737367544323206e-13 		| 0.0 		| 2.5849394142282115e-26
2.842170943040401e-14 		| 0.0 		| 4.0389678347315804e-28
3.552713678800501e-15 		| 0.0 		| 6.310887241768095e-30
4.440892098500626e-16 		| 0.0 		| 9.860761315262648e-32
5.551115123125783e-17 		| 0.0 		| 1.5407439555097887e-33
6.938893903907228e-18 		| 0.0 		| 2.407412430484045e-35
8.673617379884035e-19 		| 0.0 		| 3.76158192263132e-37
20×3 DataFrames.DataFrame
│ Row │ x           │ f_x         │ g_x         │
├─────┼─────────────┼─────────────┼─────────────┤
│ 1   │ 0.125       │ 0.00778222  │ 0.00778222  │
│ 2   │ 0.015625    │ 0.000122063 │ 0.000122063 │
│ 3   │ 0.00195313  │ 1.90735e-6  │ 1.90735e-6  │
│ 4   │ 0.000244141 │ 2.98023e-8  │ 2.98023e-8  │
│ 5   │ 3.05176e-5  │ 4.65661e-10 │ 4.65661e-10 │
│ 6   │ 3.8147e-6   │ 7.27596e-12 │ 7.27596e-12 │
│ 7   │ 4.76837e-7  │ 1.13687e-13 │ 1.13687e-13 │
│ 8   │ 5.96046e-8  │ 1.77636e-15 │ 1.77636e-15 │
│ 9   │ 7.45058e-9  │ 0.0         │ 2.77556e-17 │
│ 10  │ 9.31323e-10 │ 0.0         │ 4.33681e-19 │
│ 11  │ 1.16415e-10 │ 0.0         │ 6.77626e-21 │
│ 12  │ 1.45519e-11 │ 0.0         │ 1.05879e-22 │
│ 13  │ 1.81899e-12 │ 0.0         │ 1.65436e-24 │
│ 14  │ 2.27374e-13 │ 0.0         │ 2.58494e-26 │
│ 15  │ 2.84217e-14 │ 0.0         │ 4.03897e-28 │
│ 16  │ 3.55271e-15 │ 0.0         │ 6.31089e-30 │
│ 17  │ 4.44089e-16 │ 0.0         │ 9.86076e-32 │
│ 18  │ 5.55112e-17 │ 0.0         │ 1.54074e-33 │
│ 19  │ 6.93889e-18 │ 0.0         │ 2.40741e-35 │
│ 20  │ 8.67362e-19 │ 0.0         │ 3.76158e-37 │

[Milan Bouchet-Valat]

Le samedi 12 novembre 2016 à 05:53 -0800, swol...@gmail.com a écrit :
> Hello,
> I'm starting with Julia and wanted to use DataFrames in homeworks to
> present the data, but I've stumbled upon a problem.
> When running the below code you'll see three lists of Float64 values.
>
> Problem is when I'm showing the DataFrame I'm loosing lots of
> information, because of the display precision.
> Is there a way to change it? In Pandas I would do
> Pandas.set_option('display.precision', 20).

I'm not sure I understand what result you want, but, I don't think
there's a way to set the precision at the moment. The best solution
would be to have a mechanism in Julia Base, which would apply equally
to arrays and data frames.


Regards

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