I want my DataFrame last 3 rows to be printed bold. Below is my DataFrame structure, both in text and image (output from Jupyter Notebook) format.
# Actually, there are some more columns but it's not necessary to put them all here.
# These columns are enough to give an example.
epoch loss accuracy f1_m precision_m recall_m lr
1 1.0 5.104000 0.494600 0.458400 0.588500 0.403900 0.001
2 2.0 3.313200 0.801000 0.799500 0.828500 0.772600 0.001
3 3.0 3.063600 0.825000 0.824400 0.852900 0.797700 0.001
4 4.0 2.855900 0.838900 0.838600 0.865700 0.813100 0.001
5 5.0 2.659400 0.847500 0.846100 0.876500 0.817800 0.001
6 6.0 2.490200 0.851100 0.851600 0.876800 0.827900 0.001
7 7.0 2.334100 0.854100 0.853400 0.880100 0.828200 0.001
8 8.0 2.168300 0.862000 0.861800 0.885700 0.839100 0.001
9 9.0 2.025500 0.864200 0.863800 0.888800 0.840300 0.001
10 10.0 1.900300 0.864100 0.863900 0.889100 0.840200 0.001
11 11.0 1.774600 0.866300 0.866200 0.888800 0.844700 0.001
12 12.0 1.668100 0.867000 0.866000 0.891700 0.841700 0.001
13 13.0 1.557800 0.869900 0.869600 0.893500 0.846900 0.001
14 14.0 1.459500 0.871900 0.872000 0.895900 0.849400 0.001
15 15.0 1.386500 0.869000 0.868600 0.892800 0.845700 0.001
16 16.0 1.294400 0.872900 0.873000 0.895800 0.851400 0.001
17 17.0 1.210600 0.876000 0.875700 0.898500 0.853900 0.001
18 18.0 1.156100 0.875800 0.875600 0.897800 0.854500 0.001
19 19.0 1.100800 0.872800 0.872100 0.897200 0.848300 0.001
20 20.0 1.042000 0.875000 0.875200 0.897100 0.854400 0.001
21 21.0 0.991800 0.875700 0.876400 0.899100 0.854900 0.001
22 22.0 0.942500 0.878600 0.878300 0.900800 0.856900 0.001
23 23.0 0.896600 0.878800 0.878400 0.901900 0.856200 0.001
24 24.0 0.857100 0.880500 0.880200 0.901800 0.859700 0.001
25 25.0 0.826900 0.878600 0.878400 0.900600 0.857300 0.001
26 26.0 0.795000 0.878600 0.878100 0.901900 0.855600 0.001
27 27.0 0.778700 0.876300 0.875800 0.900400 0.852500 0.001
28 28.0 0.750800 0.876100 0.875700 0.899300 0.853300 0.001
29 29.0 0.718600 0.878900 0.878900 0.901900 0.857000 0.001
30 30.0 0.707000 0.876000 0.875400 0.899100 0.852900 0.001
31 31.0 0.694900 0.875800 0.875900 0.900000 0.853100 0.001
32 32.0 0.665100 0.879300 0.879100 0.900600 0.858600 0.001
33 33.0 0.657700 0.875600 0.875400 0.899700 0.852500 0.001
34 34.0 0.637700 0.878100 0.878100 0.901000 0.856300 0.001
35 35.0 0.618600 0.880100 0.879500 0.902900 0.857300 0.001
36 36.0 0.601200 0.880400 0.880600 0.902700 0.859600 0.001
37 37.0 0.589900 0.882300 0.882100 0.903400 0.861800 0.001
38 38.0 0.580500 0.880400 0.880600 0.901800 0.860400 0.001
39 39.0 0.573000 0.880200 0.880300 0.902100 0.859600 0.001
40 40.0 0.555900 0.882200 0.881700 0.904700 0.859900 0.001
41 41.0 0.551200 0.880700 0.880300 0.902900 0.858800 0.001
42 42.0 0.547500 0.880400 0.879900 0.903300 0.857600 0.001
43 43.0 0.531100 0.883500 0.883500 0.905500 0.862600 0.001
44 44.0 0.537000 0.880000 0.879500 0.903300 0.856900 0.001
45 45.0 0.526200 0.883200 0.882200 0.904300 0.861200 0.001
46 46.0 0.517900 0.882000 0.882300 0.903000 0.862500 0.001
47 47.0 0.514400 0.881100 0.880900 0.902100 0.860700 0.001
48 48.0 0.505000 0.883400 0.882700 0.904800 0.861600 0.001
49 49.0 0.499200 0.883300 0.883600 0.904600 0.863500 0.001
50 50.0 0.491200 0.884600 0.884700 0.905600 0.864800 0.001
min 1.0 0.491200 0.494600 0.458400 0.588500 0.403900 0.001
max 50.0 5.104000 0.884600 0.884700 0.905600 0.864800 0.001
mean 25.5 1.285006 0.857558 0.855906 0.883479 0.832423 0.001
For starters, I have tried using 2 answers from this post code to just test if it's working for the last row, but it didn't work.
Is there any other idea to style the DataFrame?
Just in case, I attach my current full code here:
import fileinput
import glob
import pathlib
import pandas as pd
import os
import numpy as np
def readText(filename):
with open(filename, "r") as f:
data = f.readlines()
return data
# I want my DataFrame to be exported to Excel files later on
def toExcelFiles(filename, data_text):
data = []
for i, line in enumerate(data_text.split('\n')[1::2], start=1):
obj = {}
obj['epoch'] = i
for x in line.split(' - ')[2:]:
k, v = x.split(':')
obj[k] = v.lstrip()
data.append(obj)
df = pd.DataFrame(data).astype(float)
filename = filename.replace(".txt", ".xlsx")
print(filename)
df.index = np.arange(1, len(df) + 1)
df.loc['min'] = df.min()
df.loc['max'] = df.max()
df.loc['mean'] = df.mean()
df.style.applymap('font-weight: bold', subset=pd.IndexSlice[df.index[df.index=='mean'], :])
with pd.option_context('display.max_rows', None, 'display.max_columns', None): # more options can be specified also
print(df)
df.to_excel(filename)
# main
os.chdir(f'C:/Users/Dionisius/OneDrive/testresult/arsi 4/txt')
file_list = glob.glob("*.txt")
print("File_list: ", file_list)
print("*"*127)
for file in file_list:
text = readText(file) # returns list
string_epoch = ''.join(text) # mengubah list jadi string
toExcelFiles(file, string_epoch)
Sample .txt file is attached here.
