如何在 Jupyter 笔记本中设置 pandas.DataFrame.loc 的输出精度？

Question

Can the precision of the tabular output of the pandas.DataFrame.loc function be increased inside a Jupyter notebook?

I would like to see the output of the $f'_{cds}$ in the table below written with a 16 decimal digit precision:

pd.set_option('precision', 16)

Sets the output precison for pandas, but I would like to be able to set the precision just for the $f'_{cds}$ column.

This is the example dataset I am using:

h,$f' {ex}$,$f' {fwd}$,$E_{fwd}$,$E_{fwdn}$,$f' {cds}$,$E {cds}$,$E_{cdsn}$ 0.5,-0.2955202066613395,-0.5172595595568812,0.2217393528955416,0.750335672137813,-0.2833598684940762,0.01216033816726331,0.04114892279159381 0.25,-0.2955202066613395,-0.4112478682644012,0.1157276616030616,0.3916065940481806,-0.2924514766709212,0.003068729990418351,0.01038416298190755 0.125,-0.2955202066613395,-0.3543820493725782,0.05886184271123868,0.1991804329600149,-0.294751223803599,0.0007689828577405744,0.002602132918179141 0.0625,-0.2955202066613395,-0.325172396632464,0.02965218997112445,0.1003389592411367,-0.2953278482673038,0.0001923583940356965,0.0006509145219167214 0.03125,-0.2955202066613395,-0.3103980279268619,0.01487782126552234,0.05034451428416885,-0.2954721100178972,4.809664344235243e-05,0.0001627524695712948 0.015625,-0.2955202066613395,-0.3029715965360111,0.007451389874671588,0.02521448519156843,-0.2955081820601322,1.202460120736104e-05,4.068960746613514e-05 0.0078125,-0.2955202066613395,-0.2992 489646633629,0.00372875800202338,0.01261760758815544,-0.2955172004835163,3.006177823283718e-06,1.017249499533797e-05 0.00390625,-0.2955202066613395,-0.297385344322862,0.001865137661522465,0.00631137099758419,-0.295519455115155,7.515461845630789e-07,2.543129598661713e-06 0.001953125,-0.2955202066613395,-0.2964529642682692,0.000932757606929624,0.003156324291551901,-0.2955200187747096,1.878866299764859e-07,6.357826833540365e-07 0.0009765625,-0.2955202066613395,-0.2959866325476241,0.0004664258862845938,0.001578321467604782,-0.2955201596896586,4.697168093370507e-08,1.589457501548573e-07

For the example dataset, the answer from Mohit works like this:

sqrerr.loc[:, ("h","$E_{cds}$","$f'_{ex}$", "$f'_{cds}$")].style.format({"$f'_{cds}$" : '{:.16f}'})

Answer 1

Use df.style :

df.style.format('{:.16f}')

Let me know if it works

For column wise operation:

df.style.format({'A': '{:.16f}', 'D': '{:.5f}'})

Answer 2

导入 pandas 库后，将这些行添加到您的代码中

pd.set_option('precision', 0) pd.set_option('display.float_format', lambda x: '%.0f' % x)

Answer 3

df.style.format sets precision only for current output. If you call "df" once again, it'll be the same like you've imported.

Based on the answer of Malik Asad, I've added if-else conditions in lambda-function so that you could remove trailing-zeros (.0) and set literally "personal" precision for each cell with numeric-value in dataframe:

        pd.set_option('display.float_format', lambda x: '%.0f' % x 
                      if (x == x and x*10 % 10 == 0) 
                      else ('%.1f' % x if (x == x and x*100 % 10 == 0)
                      else '%.2f' % x))

Example in Python

Of course, you can improve it by adding more options.