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 │
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