qiita's Dataset for estimating age and gender from facial images IMDB- I'm trying WIKI .

full_path = meta [db] [0, 0] ["full_path"] [0]
dob = meta [db] [0, 0] ["dob"] [0]

I tried this part of the site above,

NameError: name 'db' is not defined

And an error occurred. I was wondering where this value (db) came from.
There is no particular mention of db on the page, and I am visiting.

Applicable source code

import scipy
from scipy import io
from scipy.io import wavfile
meta = scipy.io.loadmat ("wiki_crop \ wiki.mat")
full_path = meta [db] [0, 0] ["full_path"] [0]
dob = meta [db] [0, 0] ["dob"] [0]

meta = scipy.io.loadmat ("wiki_crop \\ wiki.mat")
meta</​​code></pre>
<p><br />
As a result, the contents of meta were output, and the values ​​related to db were searched, but there was nothing particularly remarkable.</p>
<pre><code>Out [2]:
{'__globals__': [],


 '__header__': b'MATLAB 5.0 MAT-file, Platform: GLNXA64, Created on: Sat Jan 16 16:25:20 2016 ',
 '__version__': '1.0',
 'wiki': array ([[(array ([[723671, 703186, 711677, ..., 720620, 723893, 713846]]), array ([[[2009, 1964, 2008, ..., 2013, 2011, 2008]],

 dtype = uint16), array ([[array (['17/10000217_1981-05-05_2009.jpg'],

 dtype = '<U31'),
         array (['48/10000548_1925-04-04_1964.jpg'],

 dtype = '<U31'),
         array (['12/100012_1948-07-03_2008.jpg'],

 dtype = '<U29'), ...,
         array (['09/9998109_1972-12-27_2013.jpg'],

 dtype = '<U30'),
         array (['00/9999400_1981-12-13_2011.jpg'],dtype = '<U30'),
         array (['80/999980_1954-06-11_2008.jpg'],

 dtype = '<U29')]],


       dtype = object), array ([[1., 1., 1., ..., 1., 1., 0.]]), array ([[array (['Sami Jauhojärvi'],

 dtype = '<U15'),
         array (['Dettmar Cramer'],

 dtype = '<U14'),
         array (['Marc Okrand'],

 dtype = '<U11'), ...,
         array (['Michael Wiesinger'],

 dtype = '<U17'),
         array (['Johann Grugger'],

 dtype = '<U14'),
         array (['Greta Van Susteren'],

 dtype = '<U18')]],

 dtype = object), array ([[array ([[111.29109473, 111.29109473, 252.66993082, 252.66993082]]),
         array ([[252.4833023, 126.68165115, 354.53192596, 228.73027481]]),
         array ([[113.52, 169.84, 366.08, 422.4]]), ...,
         array ([[169.88839786, 74.31669472, 235.2534231, 139.68171997]]),
         array ([[1, 1, 1, 1]],

 dtype = uint8),
         array ([[92.72633235, 62.0435549, 230.12083087, 199.43805342]])]],


       dtype = object), array ([[4.30096239, 2.6456395, 4.32932883, ..., 3.49430317, -inf,
         5.48691655]]), array ([[nan, 1.94924791, nan, ..., nan, nan,
                nan]]))]],


       dtype = [('dob', 'O'), ('photo_taken', 'O'), ('full_path', 'O'), ('gender', 'O'), ('name', 'O '), (' face_location ',' O '), (' face_score ',' O '), (' second_face_score ',' O ')])}

Supplemental information (FW/tool version etc.)

Environment.
OS: windows10
Anaconda
backcall 0.1.0 py35_0 anaconda
blas 1.0 mkl anaconda
bleach 2.1.4 py35_0 anaconda
ca-certificates 2019.10.16 0
certifi 2018.8.24 py35_1
colorama 0.4.1 py_0 anaconda
db 6.1.26 h6538335_0 anaconda
decorator 4.4.1 py_0 anaconda
defusedxml 0.6.0 py_0 anaconda
entrypoints 0.2.3 py35_2 anaconda
h5py 2.8.0 py35h3bdd7fb_2
hdf5 1.10.2 hac2f561_1
html5lib 1.0.1 py35_0 anaconda
icc_rt 2019.0.0 h0cc432a_1 anaconda
icu 57.1 vc14_0 [vc14] anaconda
intel-openmp 2019.5 281 anaconda
ipykernel 4.10.0 py35_0 anaconda
ipython 6.5.0 py35_0 anaconda
ipython_genutils 0.2.0 py35ha709e79_0 anaconda
ipywidgets 7.4.1 py35_0 anaconda
jedi 0.12.1 py35_0 anaconda
jinja2 2.10.3 py_0 anaconda
jpeg 9b vc14h4d7706e_1 [vc14] anaconda
jsonschema 2.6.0 py35h27d56d3_0 anaconda
jupyter 1.0.0 py35_7 anaconda
jupyter_client 5.3.3 py_0 anaconda
jupyter_console 5.2.0 py35_1 anaconda
jupyter_core 4.5.0 py_0 anaconda
libdb 6.1.26 he025d50_0 anaconda
libpng 1.6.32 vc14h5163883_3 [vc14] anaconda
m2w64-gcc-libgfortran 5.3.0 6
m2w64-gcc-libs 5.3.0 7
m2w64-gcc-libs-core 5.3.0 7
m2w64-gmp 6.1.0 2
m2w64-libwinpthread-git 5.0.0.4634.697f757 2
markupsafe 1.0 py35hfa6e2cd_1 anaconda
mistune 0.8.3 py35hfa6e2cd_1 anaconda
mkl 2019.5 281 anaconda
mkl_fft 1.0.6 py35hdbbee80_0 anaconda
mkl_random 1.0.1 py35h77b88f5_1 anaconda
msys2-conda-epoch 20160418 1
nbconvert 5.5.0 py_0 anaconda
nbformat 4.4.0 py35h908c9d9_0 anaconda
notebook 5.6.0 py35_0 anaconda
numpy 1.15.2 py35ha559c80_0 anaconda
numpy-base 1.15.2 py35h8128ebf_0 anaconda
openssl 1.0.2t vc14h62dcd97_0
pandoc 2.2.3.2 0 anaconda
pandocfilters 1.4.2 py35_1 anaconda
parso 0.5.1 py_0 anaconda
pickleshare 0.7.4 py35h2f9f535_0 anaconda
pip 10.0.1 py35_0
prometheus_client 0.7.1 py_0 anaconda
prompt_toolkit 1.0.15 py35h89c7cb4_0 anaconda
pygments 2.4.2 py_0 anaconda
pyqt 5.6.0 py35_2 anaconda
python 3.5.6 he025d50_0
python-dateutil 2.8.1 py_0 anaconda
pywin32 223 py35hfa6e2cd_1
pywinpty 0.5.4 py35_0 anaconda
pyzmq 17.0.0 py35hfa6e2cd_0 anaconda
qt 5.6.2 vc14_6 [vc14] anaconda
qtconsole 4.5.5 py_0 anaconda
scipy 1.1.0 py35h4f6bf74_1 anaconda
send2trash 1.5.0 py35_0 anaconda
setuptools 40.2.0 py35_0
simplegeneric 0.8.1 py35_2 anaconda
sip 4.19.12 py35h6538335_0 anaconda
six 1.11.0 py35_1 anaconda
terminado 0.8.1 py35_1 anaconda
testpath 0.3.1 py35h06cf69e_0 anaconda
tornado 5.1.1 py35hfa6e2cd_0 anaconda
traitlets 4.3.2 py35h09b975b_0 anaconda
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_0
wcwidth 0.1.7 py35h6e80d8a_0 anaconda
webencodings 0.5.1 py35_1 anaconda
wheel 0.31.1 py35_0
widgetsnbextension 3.4.1 py35_0 anaconda
win_unicode_console 0.5 py35h56988b5_0 anaconda
wincertstore 0.2 py35hfebbdb8_0
winpty 0.4.3 4 anaconda
zlib 1.2.11 vc14h1cdd9ab_1 [vc14] anaconda