Overview

Dataset statistics

Number of variables10
Number of observations1468
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory122.0 KiB
Average record size in memory85.1 B

Variable types

Categorical3
Text3
Numeric4

Dataset

Description광주교통공사의 역사별 안내음성 데이터로, 음성 안내 텍스트, 주변 정보 종류, 음성 안내 파일, 역사 코드, 출구 번호 정보를 제공합니다.
Author광주교통공사
URLhttps://www.data.go.kr/data/15111425/fileData.do

Alerts

호선정보 has constant value ""Constant
역사코드 is highly overall correlated with 음성파일번호 and 2 other fieldsHigh correlation
음성파일번호 is highly overall correlated with 역사코드 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 역사코드 and 2 other fieldsHigh correlation
역사명 is highly overall correlated with 역사코드 and 2 other fieldsHigh correlation
음성 안내 파일 has unique valuesUnique
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:24:52.898847
Analysis finished2023-12-12 10:24:56.453779
Duration3.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주변정보종류
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
공공기관
732 
의료기관
368 
시장, 명소
232 
시장,명소
136 

Length

Max length6
Median length4
Mean length4.4087193
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시장,명소
2nd row공공기관
3rd row의료기관
4th row의료기관
5th row의료기관

Common Values

ValueCountFrequency (%)
공공기관 732
49.9%
의료기관 368
25.1%
시장, 명소 232
 
15.8%
시장,명소 136
 
9.3%

Length

2023-12-12T19:24:56.549993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:24:56.703051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공기관 732
43.1%
의료기관 368
21.6%
시장 232
 
13.6%
명소 232
 
13.6%
시장,명소 136
 
8.0%

음성 안내 파일
Text

UNIQUE 

Distinct1468
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2023-12-12T19:24:57.065638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length70
Mean length66.205041
Min length64

Characters and Unicode

Total characters97189
Distinct characters90
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1468 ?
Unique (%)100.0%

Sample

1st rowhttps://openapi.grtc.co.kr/upload/brand/voice/1_공항역_2_일본어_287.mp3
2nd rowhttps://openapi.grtc.co.kr/upload/brand/voice/1_문화전당역_3_중국어_068.mp3
3rd rowhttps://openapi.grtc.co.kr/upload/brand/voice/1_금남로5가역_1_중국어_102.mp3
4th rowhttps://openapi.grtc.co.kr/upload/brand/voice/1_남광주역_2_중국어_043.mp3
5th rowhttps://openapi.grtc.co.kr/upload/brand/voice/1_평동역_3_영어_366.mp3
ValueCountFrequency (%)
https://openapi.grtc.co.kr/upload/brand/voice/1_공항역_2_일본어_287.mp3 1
 
0.1%
https://openapi.grtc.co.kr/upload/brand/voice/1_학동증심사입구역_3_일본어_031.mp3 1
 
0.1%
https://openapi.grtc.co.kr/upload/brand/voice/1_남광주역_1_영어_039.mp3 1
 
0.1%
https://openapi.grtc.co.kr/upload/brand/voice/1_김대중컨벤션센터역_3_중국어_267.mp3 1
 
0.1%
https://openapi.grtc.co.kr/upload/brand/voice/1_문화전당역_3_영어_068.mp3 1
 
0.1%
https://openapi.grtc.co.kr/upload/brand/voice/1_학동증심사입구역_4_영어_036.mp3 1
 
0.1%
https://openapi.grtc.co.kr/upload/brand/voice/1_문화전당역_4_중국어_072.mp3 1
 
0.1%
https://openapi.grtc.co.kr/upload/brand/voice/1_상무역_1_영어_234.mp3 1
 
0.1%
https://openapi.grtc.co.kr/upload/brand/voice/1_운천역_1_영어_219.mp3 1
 
0.1%
https://openapi.grtc.co.kr/upload/brand/voice/1_농성역_7_영어_181.mp3 1
 
0.1%
Other values (1458) 1458
99.3%
2023-12-12T19:24:57.606356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 8808
 
9.1%
p 7340
 
7.6%
_ 5872
 
6.0%
o 5872
 
6.0%
. 5872
 
6.0%
a 4404
 
4.5%
t 4404
 
4.5%
c 4404
 
4.5%
r 4404
 
4.5%
i 2936
 
3.0%
Other values (80) 42873
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 55784
57.4%
Other Punctuation 16148
 
16.6%
Other Letter 10417
 
10.7%
Decimal Number 8968
 
9.2%
Connector Punctuation 5872
 
6.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 1468
 
14.1%
역 1468
 
14.1%
국 734
 
7.0%
중 463
 
4.4%
영 367
 
3.5%
한 367
 
3.5%
본 367
 
3.5%
일 367
 
3.5%
남 256
 
2.5%
정 208
 
2.0%
Other values (47) 4352
41.8%
Lowercase Letter
ValueCountFrequency (%)
p 7340
13.2%
o 5872
10.5%
a 4404
 
7.9%
t 4404
 
7.9%
c 4404
 
7.9%
r 4404
 
7.9%
i 2936
 
5.3%
d 2936
 
5.3%
n 2936
 
5.3%
e 2936
 
5.3%
Other values (9) 13212
23.7%
Decimal Number
ValueCountFrequency (%)
1 2496
27.8%
3 2352
26.2%
2 1008
11.2%
0 696
 
7.8%
4 660
 
7.4%
5 532
 
5.9%
6 412
 
4.6%
7 284
 
3.2%
9 264
 
2.9%
8 264
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/ 8808
54.5%
. 5872
36.4%
: 1468
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 5872
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 55784
57.4%
Common 30988
31.9%
Hangul 10417
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 1468
 
14.1%
역 1468
 
14.1%
국 734
 
7.0%
중 463
 
4.4%
영 367
 
3.5%
한 367
 
3.5%
본 367
 
3.5%
일 367
 
3.5%
남 256
 
2.5%
정 208
 
2.0%
Other values (47) 4352
41.8%
Latin
ValueCountFrequency (%)
p 7340
13.2%
o 5872
10.5%
a 4404
 
7.9%
t 4404
 
7.9%
c 4404
 
7.9%
r 4404
 
7.9%
i 2936
 
5.3%
d 2936
 
5.3%
n 2936
 
5.3%
e 2936
 
5.3%
Other values (9) 13212
23.7%
Common
ValueCountFrequency (%)
/ 8808
28.4%
_ 5872
18.9%
. 5872
18.9%
1 2496
 
8.1%
3 2352
 
7.6%
: 1468
 
4.7%
2 1008
 
3.3%
0 696
 
2.2%
4 660
 
2.1%
5 532
 
1.7%
Other values (4) 1224
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86772
89.3%
Hangul 10417
 
10.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 8808
 
10.2%
p 7340
 
8.5%
_ 5872
 
6.8%
o 5872
 
6.8%
. 5872
 
6.8%
a 4404
 
5.1%
t 4404
 
5.1%
c 4404
 
5.1%
r 4404
 
5.1%
i 2936
 
3.4%
Other values (23) 32456
37.4%
Hangul
ValueCountFrequency (%)
어 1468
 
14.1%
역 1468
 
14.1%
국 734
 
7.0%
중 463
 
4.4%
영 367
 
3.5%
한 367
 
3.5%
본 367
 
3.5%
일 367
 
3.5%
남 256
 
2.5%
정 208
 
2.0%
Other values (47) 4352
41.8%

역사코드
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.74387
Minimum100
Maximum119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-12T19:24:57.777451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile101
Q1105
median110
Q3114
95-th percentile118
Maximum119
Range19
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.3639011
Coefficient of variation (CV)0.048876544
Kurtosis-1.195678
Mean109.74387
Median Absolute Deviation (MAD)5
Skewness-0.0085243365
Sum161104
Variance28.771435
MonotonicityNot monotonic
2023-12-12T19:24:57.934932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
109 112
 
7.6%
115 96
 
6.5%
114 96
 
6.5%
113 96
 
6.5%
103 96
 
6.5%
106 96
 
6.5%
104 92
 
6.3%
117 80
 
5.4%
110 64
 
4.4%
101 64
 
4.4%
Other values (10) 576
39.2%
ValueCountFrequency (%)
100 16
 
1.1%
101 64
4.4%
102 64
4.4%
103 96
6.5%
104 92
6.3%
105 64
4.4%
106 96
6.5%
107 64
4.4%
108 64
4.4%
109 112
7.6%
ValueCountFrequency (%)
119 48
3.3%
118 64
4.4%
117 80
5.4%
116 64
4.4%
115 96
6.5%
114 96
6.5%
113 96
6.5%
112 64
4.4%
111 64
4.4%
110 64
4.4%

출구번호
Real number (ℝ)

Distinct7
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0054496
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-12T19:24:58.073227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5734584
Coefficient of variation (CV)0.52353511
Kurtosis-0.6824043
Mean3.0054496
Median Absolute Deviation (MAD)1
Skewness0.43256438
Sum4412
Variance2.4757712
MonotonicityNot monotonic
2023-12-12T19:24:58.266736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 316
21.5%
2 304
20.7%
3 304
20.7%
4 288
19.6%
5 128
8.7%
6 112
 
7.6%
7 16
 
1.1%
ValueCountFrequency (%)
1 316
21.5%
2 304
20.7%
3 304
20.7%
4 288
19.6%
5 128
8.7%
6 112
 
7.6%
7 16
 
1.1%
ValueCountFrequency (%)
7 16
 
1.1%
6 112
 
7.6%
5 128
8.7%
4 288
19.6%
3 304
20.7%
2 304
20.7%
1 316
21.5%

호선정보
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
1
1468 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1468
100.0%

Length

2023-12-12T19:24:58.413940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:24:58.579462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1468
100.0%

역사명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
농성역
112 
김대중컨벤션센터역
 
96
상무역
 
96
남광주역
 
96
금남로5가역
 
96
Other values (15)
972 

Length

Max length9
Median length8
Mean length4.4550409
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공항역
2nd row문화전당역
3rd row금남로5가역
4th row남광주역
5th row평동역

Common Values

ValueCountFrequency (%)
농성역 112
 
7.6%
김대중컨벤션센터역 96
 
6.5%
상무역 96
 
6.5%
남광주역 96
 
6.5%
금남로5가역 96
 
6.5%
공항역 96
 
6.5%
문화전당역 92
 
6.3%
광주송정역 80
 
5.4%
양동시장역 64
 
4.4%
소태역 64
 
4.4%
Other values (10) 576
39.2%

Length

2023-12-12T19:24:58.720966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
농성역 112
 
7.6%
상무역 96
 
6.5%
남광주역 96
 
6.5%
금남로5가역 96
 
6.5%
공항역 96
 
6.5%
김대중컨벤션센터역 96
 
6.5%
문화전당역 92
 
6.3%
광주송정역 80
 
5.4%
학동증심사입구역 64
 
4.4%
돌고개역 64
 
4.4%
Other values (10) 576
39.2%

음성파일번호
Real number (ℝ)

HIGH CORRELATION 

Distinct367
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184
Minimum1
Maximum367
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-12T19:24:58.865222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19
Q192
median184
Q3276
95-th percentile349
Maximum367
Range366
Interquartile range (IQR)184

Descriptive statistics

Standard deviation105.97948
Coefficient of variation (CV)0.57597546
Kurtosis-1.2000168
Mean184
Median Absolute Deviation (MAD)92
Skewness0
Sum270112
Variance11231.651
MonotonicityNot monotonic
2023-12-12T19:24:59.058613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
287 4
 
0.3%
326 4
 
0.3%
341 4
 
0.3%
306 4
 
0.3%
146 4
 
0.3%
173 4
 
0.3%
311 4
 
0.3%
360 4
 
0.3%
295 4
 
0.3%
27 4
 
0.3%
Other values (357) 1428
97.3%
ValueCountFrequency (%)
1 4
0.3%
2 4
0.3%
3 4
0.3%
4 4
0.3%
5 4
0.3%
6 4
0.3%
7 4
0.3%
8 4
0.3%
9 4
0.3%
10 4
0.3%
ValueCountFrequency (%)
367 4
0.3%
366 4
0.3%
365 4
0.3%
364 4
0.3%
363 4
0.3%
362 4
0.3%
361 4
0.3%
360 4
0.3%
359 4
0.3%
358 4
0.3%

음성 안내 텍스트
Text

Distinct1275
Distinct (%)86.9%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2023-12-12T19:24:59.545286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length803
Median length540
Mean length293.11035
Min length1

Characters and Unicode

Total characters430286
Distinct characters1253
Distinct categories13 ?
Distinct scripts7 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1192 ?
Unique (%)81.2%

Sample

1st row空港は約300ｍ地点に光州空港があり、利用客の便宜をるため、道に雪と雨が避けられるキャノピが設置されている。周りには小公園があり、休息の場となっている。また、ヨンサンガン自車道と西倉トゥルニョッススキ祭りで美しい風景が鑑賞できる。近隣の市場、名所は2番出口を出て、190m直進して駐車場へ245m行けば光州空港があり、忠壯路通りには有名なグンゾンゼガがある。
2nd row文化殿堂站建于此，不但保留了光州全南道本和尙武的容貌，且所有出口都建立于立洲文化殿堂之上。因周的景点不，且回中的忠祭每年都在此行，文化殿堂站的人火朝天。附近的公共机광주광역시동구청。2口向步行90米后，向南步行60米, 再向步行130米可到目的地。
3rd row南路5街站的地下二保存着光州生立的片和影海等料，散着令游客不的史光彩。在，此站矗立着座座高大厦，因此交通需求正在不上升。附近的机맑은 머리 김동욱신경 의원。位于3口右。
4th row由于光州全南地方兵, 全南大，朝大院，南光州市，南光州站早到水。被的全南光州站被改建路公供居民活休息。附近的机연합의원。2口向西南方向步行500米可到目的地。
5th rowPyeongdong Station, which starts from the west side of Line 1 and towards downtown of Gwangju, is a ground station and has a bright atmosphere due to characteristic of ground station. It has a lot of commuting flow, and has a good transfer system such as shuttle bus service and free bicycle service. There is also a course where you can take a subway or bicycle to see famous places around the Hwangnyong River and 송산 amusement park.The nearest medical institution is the Pyeongdong Bangbu Clinic, come out from Exit 3 and cross a crosswalk towards KIA Gwangju Shipping Center, take a bus at Pyeongdong Station (East) Bus Stop and get off at Okdong Bus Stop then move 30m towards Pyeongdong pharmacy.
ValueCountFrequency (%)
and 1668
 
2.9%
the 1459
 
2.5%
is 1090
 
1.9%
있습니다 935
 
1.6%
station 835
 
1.4%
of 769
 
1.3%
exit 623
 
1.1%
출구로 616
 
1.1%
from 598
 
1.0%
a 584
 
1.0%
Other values (3345) 49089
84.2%
2023-12-12T19:25:00.239633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58926
 
13.7%
e 16198
 
3.8%
a 15111
 
3.5%
t 14533
 
3.4%
n 14423
 
3.4%
o 13851
 
3.2%
i 11699
 
2.7%
s 9293
 
2.2%
r 9120
 
2.1%
m 5772
 
1.3%
Other values (1243) 261360
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174470
40.5%
Lowercase Letter 158479
36.8%
Space Separator 58926
 
13.7%
Decimal Number 13644
 
3.2%
Other Punctuation 13197
 
3.1%
Uppercase Letter 9890
 
2.3%
Dash Punctuation 780
 
0.2%
Close Punctuation 372
 
0.1%
Open Punctuation 370
 
0.1%
Initial Punctuation 87
 
< 0.1%
Other values (3) 71
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 2875
 
1.6%
的 1928
 
1.1%
다 1845
 
1.1%
ン 1833
 
1.1%
이 1829
 
1.0%
있 1820
 
1.0%
て 1770
 
1.0%
の 1738
 
1.0%
니 1713
 
1.0%
が 1710
 
1.0%
Other values (1150) 155409
89.1%
Lowercase Letter
ValueCountFrequency (%)
e 16198
 
10.2%
a 15111
 
9.5%
t 14533
 
9.2%
n 14423
 
9.1%
o 13851
 
8.7%
i 11699
 
7.4%
s 9293
 
5.9%
r 9120
 
5.8%
m 5772
 
3.6%
l 5759
 
3.6%
Other values (17) 42720
27.0%
Uppercase Letter
ValueCountFrequency (%)
S 1569
15.9%
G 862
 
8.7%
C 837
 
8.5%
E 734
 
7.4%
T 663
 
6.7%
A 625
 
6.3%
H 561
 
5.7%
M 514
 
5.2%
P 497
 
5.0%
N 339
 
3.4%
Other values (15) 2689
27.2%
Decimal Number
ValueCountFrequency (%)
1 2492
18.3%
0 2271
16.6%
2 1796
13.2%
5 1598
11.7%
4 1327
9.7%
3 1311
9.6%
6 1103
8.1%
9 748
 
5.5%
8 532
 
3.9%
7 394
 
2.9%
Other values (6) 72
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 3147
23.8%
. 3130
23.7%
。 2936
22.2%
、 2028
15.4%
， 1323
10.0%
" 330
 
2.5%
' 236
 
1.8%
· 36
 
0.3%
: 18
 
0.1%
/ 10
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 198
53.2%
」 107
28.8%
） 67
 
18.0%
Open Punctuation
ValueCountFrequency (%)
( 195
52.7%
「 107
28.9%
（ 68
 
18.4%
Final Punctuation
ValueCountFrequency (%)
’ 51
76.1%
” 16
 
23.9%
Initial Punctuation
ValueCountFrequency (%)
‘ 51
58.6%
“ 36
41.4%
Space Separator
ValueCountFrequency (%)
58926
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 780
100.0%
Other Symbol
ValueCountFrequency (%)
㎞ 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 168368
39.1%
Common 87447
20.3%
Hangul 85293
19.8%
Han 57530
 
13.4%
Hiragana 21920
 
5.1%
Katakana 9727
 
2.3%
Cyrillic 1
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
的 1928
 
3.4%
口 1324
 
2.3%
出 1201
 
2.1%
光 1181
 
2.1%
向 1034
 
1.8%
州 971
 
1.7%
近 952
 
1.7%
站 951
 
1.7%
公 882
 
1.5%
地 866
 
1.5%
Other values (549) 46240
80.4%
Hangul
ValueCountFrequency (%)
로 2875
 
3.4%
다 1845
 
2.2%
이 1829
 
2.1%
있 1820
 
2.1%
니 1713
 
2.0%
정 1656
 
1.9%
가 1641
 
1.9%
주 1543
 
1.8%
번 1534
 
1.8%
습 1469
 
1.7%
Other values (463) 67368
79.0%
Katakana
ValueCountFrequency (%)
ン 1833
 
18.8%
ス 497
 
5.1%
ル 456
 
4.7%
ム 360
 
3.7%
サ 290
 
3.0%
バ 282
 
2.9%
キ 280
 
2.9%
ョ 273
 
2.8%
タ 259
 
2.7%
ジ 253
 
2.6%
Other values (66) 4944
50.8%
Hiragana
ValueCountFrequency (%)
て 1770
 
8.1%
の 1738
 
7.9%
が 1710
 
7.8%
る 1452
 
6.6%
に 1295
 
5.9%
は 1094
 
5.0%
と 1030
 
4.7%
り 956
 
4.4%
で 940
 
4.3%
あ 918
 
4.2%
Other values (42) 9017
41.1%
Latin
ValueCountFrequency (%)
e 16198
 
9.6%
a 15111
 
9.0%
t 14533
 
8.6%
n 14423
 
8.6%
o 13851
 
8.2%
i 11699
 
6.9%
s 9293
 
5.5%
r 9120
 
5.4%
m 5772
 
3.4%
l 5759
 
3.4%
Other values (41) 52609
31.2%
Common
ValueCountFrequency (%)
58926
67.4%
, 3147
 
3.6%
. 3130
 
3.6%
。 2936
 
3.4%
1 2492
 
2.8%
0 2271
 
2.6%
、 2028
 
2.3%
2 1796
 
2.1%
5 1598
 
1.8%
4 1327
 
1.5%
Other values (31) 7796
 
8.9%
Cyrillic
ValueCountFrequency (%)
М 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 248789
57.8%
Hangul 85293
 
19.8%
CJK 57430
 
13.3%
Hiragana 21920
 
5.1%
Katakana 9727
 
2.3%
None 6869
 
1.6%
Punctuation 154
 
< 0.1%
CJK Compat Ideographs 100
 
< 0.1%
CJK Compat 3
 
< 0.1%
Cyrillic 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58926
23.7%
e 16198
 
6.5%
a 15111
 
6.1%
t 14533
 
5.8%
n 14423
 
5.8%
o 13851
 
5.6%
i 11699
 
4.7%
s 9293
 
3.7%
r 9120
 
3.7%
m 5772
 
2.3%
Other values (60) 79863
32.1%
None
ValueCountFrequency (%)
。 2936
42.7%
、 2028
29.5%
， 1323
19.3%
ｍ 121
 
1.8%
「 107
 
1.6%
」 107
 
1.6%
（ 68
 
1.0%
） 67
 
1.0%
· 36
 
0.5%
１ 22
 
0.3%
Other values (7) 54
 
0.8%
Hangul
ValueCountFrequency (%)
로 2875
 
3.4%
다 1845
 
2.2%
이 1829
 
2.1%
있 1820
 
2.1%
니 1713
 
2.0%
정 1656
 
1.9%
가 1641
 
1.9%
주 1543
 
1.8%
번 1534
 
1.8%
습 1469
 
1.7%
Other values (463) 67368
79.0%
CJK
ValueCountFrequency (%)
的 1928
 
3.4%
口 1324
 
2.3%
出 1201
 
2.1%
光 1181
 
2.1%
向 1034
 
1.8%
州 971
 
1.7%
近 952
 
1.7%
站 951
 
1.7%
公 882
 
1.5%
地 866
 
1.5%
Other values (544) 46140
80.3%
Katakana
ValueCountFrequency (%)
ン 1833
 
18.8%
ス 497
 
5.1%
ル 456
 
4.7%
ム 360
 
3.7%
サ 290
 
3.0%
バ 282
 
2.9%
キ 280
 
2.9%
ョ 273
 
2.8%
タ 259
 
2.7%
ジ 253
 
2.6%
Other values (66) 4944
50.8%
Hiragana
ValueCountFrequency (%)
て 1770
 
8.1%
の 1738
 
7.9%
が 1710
 
7.8%
る 1452
 
6.6%
に 1295
 
5.9%
は 1094
 
5.0%
と 1030
 
4.7%
り 956
 
4.4%
で 940
 
4.3%
あ 918
 
4.2%
Other values (42) 9017
41.1%
CJK Compat Ideographs
ValueCountFrequency (%)
良 79
79.0%
李 16
 
16.0%
龍 2
 
2.0%
柳 2
 
2.0%
林 1
 
1.0%
Punctuation
ValueCountFrequency (%)
’ 51
33.1%
‘ 51
33.1%
“ 36
23.4%
” 16
 
10.4%
CJK Compat
ValueCountFrequency (%)
㎞ 3
100.0%
Cyrillic
ValueCountFrequency (%)
М 1
100.0%

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1468
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean734.5
Minimum1
Maximum1468
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-12T19:25:00.447999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile74.35
Q1367.75
median734.5
Q31101.25
95-th percentile1394.65
Maximum1468
Range1467
Interquartile range (IQR)733.5

Descriptive statistics

Standard deviation423.91941
Coefficient of variation (CV)0.57715372
Kurtosis-1.2
Mean734.5
Median Absolute Deviation (MAD)367
Skewness0
Sum1078246
Variance179707.67
MonotonicityNot monotonic
2023-12-12T19:25:00.631619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1148 1
 
0.1%
640 1
 
0.1%
124 1
 
0.1%
511 1
 
0.1%
154 1
 
0.1%
1067 1
 
0.1%
270 1
 
0.1%
142 1
 
0.1%
287 1
 
0.1%
934 1
 
0.1%
Other values (1458) 1458
99.3%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1468 1
0.1%
1467 1
0.1%
1466 1
0.1%
1465 1
0.1%
1464 1
0.1%
1463 1
0.1%
1462 1
0.1%
1461 1
0.1%
1460 1
0.1%
1459 1
0.1%

주변정보 고유번호
Text

Distinct367
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2023-12-12T19:25:00.886856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length17.640327
Min length13

Characters and Unicode

Total characters25896
Distinct characters65
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1_공항역_2_시장,명소_001
2nd row1_문화전당역_3_공공기관_001
3rd row1_금남로5가역_1_의료기관_001
4th row1_남광주역_2_의료기관_001
5th row1_평동역_3_의료기관_001
ValueCountFrequency (%)
명소_001 144
 
8.9%
1_공항역_2_시장,명소_001 4
 
0.2%
1_학동증심사입구역_3_공공기관_002 4
 
0.2%
1_송정공원역_1_의료기관_001 4
 
0.2%
1_돌고개역_2_의료기관_001 4
 
0.2%
1_농성역_5_공공기관_002 4
 
0.2%
1_송정공원역_2_시장,명소_001 4
 
0.2%
1_평동역_2_공공기관_001 4
 
0.2%
1_공항역_4_시장,명소_001 4
 
0.2%
1_학동증심사입구역_2_의료기관_001 4
 
0.2%
Other values (358) 1432
88.8%
2023-12-12T19:25:01.292130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 5872
22.7%
0 2932
 
11.3%
1 2876
 
11.1%
공 1616
 
6.2%
역 1464
 
5.7%
관 1096
 
4.2%
기 1096
 
4.2%
2 672
 
2.6%
시 436
 
1.7%
장 436
 
1.7%
Other values (55) 7400
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12032
46.5%
Decimal Number 7488
28.9%
Connector Punctuation 5872
22.7%
Other Punctuation 360
 
1.4%
Space Separator 144
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 1616
 
13.4%
역 1464
 
12.2%
관 1096
 
9.1%
기 1096
 
9.1%
시 436
 
3.6%
장 436
 
3.6%
소 424
 
3.5%
료 368
 
3.1%
의 368
 
3.1%
명 360
 
3.0%
Other values (44) 4368
36.3%
Decimal Number
ValueCountFrequency (%)
0 2932
39.2%
1 2876
38.4%
2 672
 
9.0%
4 352
 
4.7%
3 304
 
4.1%
5 224
 
3.0%
6 112
 
1.5%
7 16
 
0.2%
Connector Punctuation
ValueCountFrequency (%)
_ 5872
100.0%
Other Punctuation
ValueCountFrequency (%)
, 360
100.0%
Space Separator
ValueCountFrequency (%)
144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13864
53.5%
Hangul 12032
46.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 1616
 
13.4%
역 1464
 
12.2%
관 1096
 
9.1%
기 1096
 
9.1%
시 436
 
3.6%
장 436
 
3.6%
소 424
 
3.5%
료 368
 
3.1%
의 368
 
3.1%
명 360
 
3.0%
Other values (44) 4368
36.3%
Common
ValueCountFrequency (%)
_ 5872
42.4%
0 2932
21.1%
1 2876
20.7%
2 672
 
4.8%
, 360
 
2.6%
4 352
 
2.5%
3 304
 
2.2%
5 224
 
1.6%
144
 
1.0%
6 112
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13864
53.5%
Hangul 12032
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 5872
42.4%
0 2932
21.1%
1 2876
20.7%
2 672
 
4.8%
, 360
 
2.6%
4 352
 
2.5%
3 304
 
2.2%
5 224
 
1.6%
144
 
1.0%
6 112
 
0.8%
Hangul
ValueCountFrequency (%)
공 1616
 
13.4%
역 1464
 
12.2%
관 1096
 
9.1%
기 1096
 
9.1%
시 436
 
3.6%
장 436
 
3.6%
소 424
 
3.5%
료 368
 
3.1%
의 368
 
3.1%
명 360
 
3.0%
Other values (44) 4368
36.3%

Interactions

2023-12-12T19:24:55.641348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:54.273687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:54.761017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:55.198959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:55.757393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:54.385411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:54.876061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:55.304365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:55.876897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:54.505886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:54.978091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:55.424734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:55.999532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:54.636532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:55.081340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:55.534520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:25:01.399588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주변정보종류역사코드출구번호역사명음성파일번호연번
주변정보종류1.0000.3480.0000.5090.3250.325
역사코드0.3481.0000.2961.0000.9890.990
출구번호0.0000.2961.0000.4780.3020.303
역사명0.5091.0000.4781.0000.9960.996
음성파일번호0.3250.9890.3020.9961.0001.000
연번0.3250.9900.3030.9961.0001.000
2023-12-12T19:25:01.538346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역사명주변정보종류
역사명1.0000.261
주변정보종류0.2611.000
2023-12-12T19:25:01.670516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역사코드출구번호음성파일번호연번주변정보종류역사명
역사코드1.000-0.0120.9980.9980.2140.997
출구번호-0.0121.0000.0390.0390.0000.228
음성파일번호0.9980.0391.0001.0000.1990.888
연번0.9980.0391.0001.0000.1990.891
주변정보종류0.2140.0000.1990.1991.0000.261
역사명0.9970.2280.8880.8910.2611.000

Missing values

2023-12-12T19:24:56.185743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:24:56.378116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

주변정보종류음성 안내 파일역사코드출구번호호선정보역사명음성파일번호음성 안내 텍스트연번주변정보 고유번호
0시장,명소https://openapi.grtc.co.kr/upload/brand/voice/1_공항역_2_일본어_287.mp311521공항역287空港は約300ｍ地点に光州空港があり、利用客の便宜をるため、道に雪と雨が避けられるキャノピが設置されている。周りには小公園があり、休息の場となっている。また、ヨンサンガン自車道と西倉トゥルニョッススキ祭りで美しい風景が鑑賞できる。近隣の市場、名所は2番出口を出て、190m直進して駐車場へ245m行けば光州空港があり、忠壯路通りには有名なグンゾンゼガがある。11481_공항역_2_시장,명소_001
1공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_문화전당역_3_중국어_068.mp310431문화전당역68文化殿堂站建于此，不但保留了光州全南道本和尙武的容貌，且所有出口都建立于立洲文化殿堂之上。因周的景点不，且回中的忠祭每年都在此行，文化殿堂站的人火朝天。附近的公共机광주광역시동구청。2口向步行90米后，向南步行60米, 再向步行130米可到目的地。2711_문화전당역_3_공공기관_001
2의료기관https://openapi.grtc.co.kr/upload/brand/voice/1_금남로5가역_1_중국어_102.mp310611금남로5가역102南路5街站的地下二保存着光州生立的片和影海等料，散着令游客不的史光彩。在，此站矗立着座座高大厦，因此交通需求正在不上升。附近的机맑은 머리 김동욱신경 의원。位于3口右。4071_금남로5가역_1_의료기관_001
3의료기관https://openapi.grtc.co.kr/upload/brand/voice/1_남광주역_2_중국어_043.mp310321남광주역43由于光州全南地方兵, 全南大，朝大院，南光州市，南光州站早到水。被的全南光州站被改建路公供居民活休息。附近的机연합의원。2口向西南方向步行500米可到目的地。1711_남광주역_2_의료기관_001
4의료기관https://openapi.grtc.co.kr/upload/brand/voice/1_평동역_3_영어_366.mp311931평동역366Pyeongdong Station, which starts from the west side of Line 1 and towards downtown of Gwangju, is a ground station and has a bright atmosphere due to characteristic of ground station. It has a lot of commuting flow, and has a good transfer system such as shuttle bus service and free bicycle service. There is also a course where you can take a subway or bicycle to see famous places around the Hwangnyong River and 송산 amusement park.The nearest medical institution is the Pyeongdong Bangbu Clinic, come out from Exit 3 and cross a crosswalk towards KIA Gwangju Shipping Center, take a bus at Pyeongdong Station (East) Bus Stop and get off at Okdong Bus Stop then move 30m towards Pyeongdong pharmacy.14621_평동역_3_의료기관_001
5공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_광주송정역_3_한국어_329.mp311731광주송정역329광주송정역은 호남고속철도와 수서발고속철도와 연계하여 도심으로 가는 빠른 접근성을 가지고 있습니다. 4번 출구에는 알렉산드로 멘디니가 설계한 캐노피 ‘빛의 꽃’ 이 방문객을 반기고 있습니다. 광주송정역 주변에는 송정5일장이 서고 있으며, 1913송정역시장은 현대적 트렌드로 리모델링 하여 관광객의 눈과 입을 사로잡고 있습니다. 인근 공공기관으로 3번 출구로 들어가서 1번 출구로 나와 송정공원역방향으로 99m 이동 후 아이비플라워에서 카페 아우라 방향으로 직진 후 송정로1번길을 따라 486m 직진하면 송정중학교가 있습니다.인근 버스 정류장은 신동사거리 방면 정류장으로 3번 출구에서 5번 출구로 나와 올리브영 방향으로 54m 떨어져있습니다. 주요 버스는 160, 송정 29 버스가 있습니다.13131_광주송정역_3_공공기관_002
6공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_남광주역_6_일본어_058.mp310361남광주역58南光州は光州地方兵務、全南大、朝鮮大病院があって流動人口が多く、南光州市場があって夜明けから夜まで人が多い。慶全本線南光州線敷地がプルンキル公園として整い、住民たちが利用できる名所になった。近隣の公共機は6番出口を出て5番出口から右折して直進すれば朝鮮大病院がある。2321_남광주역_6_공공기관_002
7시장, 명소https://openapi.grtc.co.kr/upload/brand/voice/1_남광주역_3_영어_048.mp310331남광주역48Namgwangju Station is crowded from dawn to night because it has Namgwangju market and it has a large floating population because of Gwangju Regional Military Manpower Administration, Jeonnam University, and Chosun University Hospital. The site of Namgwangju Station on the Gyeongjeon Line has been constructed as Pulungil Park, making it a popular attraction for residents.A nearby market, a famous place is Namgwangju Agricultural and Fishery Products Shopping Mall. Use Exit 3 and take a left at Chonnam National University Hospital intersection and go straight 204m.1901_남광주역_3_시장, 명소_001
8공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_공항역_3_일본어_288.mp311531공항역288空港は約300ｍ地点に光州空港があり、利用客の便宜をるため、道に雪と雨が避けられるキャノピが設置されている。周りには小公園があり、休息の場となっている。また、ヨンサンガン自車道と西倉トゥルニョッススキ祭りで美しい風景が鑑賞できる。近隣の公共機は3番出口に入り、5番出口を出て、松汀公園の方向に松汀局まで542m直進する。また、松汀洞小校まで約60m移動して左側に176m移動すれば松汀交番がある。11521_공항역_3_공공기관_001
9시장,명소https://openapi.grtc.co.kr/upload/brand/voice/1_광주송정역_5_일본어_339.mp311751광주송정역339光州松汀は湖南高速道と水西高速道と連携して都心に早くいくことができて、接近性が良い。4番出口にはアレッサンドロメンディニが設計したキャノピの「光の花」が訪問客を迎える。光州松汀は松汀オイルザンが開かれており、1913松汀市場は現代的トレンドとしてリモデリングして光客の興味を引く。近隣の市場、名所は5番出口に入り、1番出口を出て、ユミョンゾンノ局の方面に22ｍ移動する。また、オフィスセルスパマケットの方面に約60ｍ移動してムグンファガラスペイントの方面へ304m以に松汀トッカルビ通りがある。13561_광주송정역_5_시장,명소_001
주변정보종류음성 안내 파일역사코드출구번호호선정보역사명음성파일번호음성 안내 텍스트연번주변정보 고유번호
1458시장, 명소https://openapi.grtc.co.kr/upload/brand/voice/1_남광주역_1_한국어_040.mp310311남광주역40남광주역은 광주지방병무청, 전남대, 조선대 병원을 끼고 있어 유동인구가 많고 남광주시장이 있어 새벽부터 밤까지 사람들이 붐빕니다. 경전선 남광주역 폐선부지가 푸른길공원으로 조성되어 주민들이 이용할 수 있는 명소가 되었습니다.인근 시장, 명소로는 1번 출구로 나와 3번 출구 방면으로 200m 이내에 남광주종합시장이 있습니다. 남광주역 1번출구 인근 버스정류장은 조선대병원방면 남광주사거리 정류장으로 주요 버스는 수완12번, 운림50번 버스가 있습니다.1571_남광주역_1_시장, 명소_001
1459공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_남광주역_2_중국어_042.mp310321남광주역42由于光州全南地方兵, 全南大，朝大院，南光州市，南光州站早到水。被的全南光州站被改建路公供居民活休息。附近的公共机봉선 119안전센터。2口向西南方向步行600米后，向南步行550米可到目的地。1671_남광주역_2_공공기관_002
1460공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_상무역_2_한국어_237.mp311321상무역237상무역은 주거, 업무, 상업시설이 밀집되어 있습니다. 광송간도로, 제2순환도로 등의 편리한 교통망과 다양한 편의시설이 갖춰져 유동 인구가 많기 때문에 주차 시설과 자전거 보관소를 운영하고 있으며 도로 횡단보도의 기능을 하여 출입구 및 연결 통로 등 이용에 편리합니다.인근 공공기관은 2번 출구로 들어가 4번 출구로 나와 스타벅스 상무역점 방향으로 92m 직진 후 파리바게뜨 상무역점에서 라인동산아파트 방향으로 416m 직진 이동하여 치평동행정복지센터 방향으로 횡단보도 1개를 건너면 치평초등학교가 위치해 있습니다.인근 버스정류장은 2번 출구에서 김대중컨벤션센터역 방향으로 60m 떨어진 곳에 위치한 상무지구입구방면 정류장으로 주요 버스는 송정19, 160이 있습니다.9451_상무역_2_공공기관_002
1461공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_운천역_1_중국어_216.mp311211운천역216云泉站周的云泉湖，5.18念公，无寺倦被灰暗色建筑所包的市中心的居民提供了休息的空。尙武路周有小模近生活施居民提供便利。附近的公共机상무고등학교。4口向北步行20米，在운천역(북)站乘坐마을760公共汽，在상무고站下可到目的地。8631_운천역_1_공공기관_001
1462공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_문화전당역_3_중국어_069.mp310431문화전당역69文化殿堂站建于此，不但保留了光州全南道本和尙武的容貌，且所有出口都建立于立洲文化殿堂之上。因周的景点不，且回中的忠祭每年都在此行，文化殿堂站的人火朝天。附近的公共机광주동부경찰서。4口向西北方向步行130米后，向北方向步行130米可到目的地。2751_문화전당역_3_공공기관_002
1463의료기관https://openapi.grtc.co.kr/upload/brand/voice/1_금남로5가역_5_일본어_118.mp310651금남로5가역118錦南路5街は地下2階に光州生立運動の資料や映ポスタなどが整っている空間が造成されており、多くの著名人が訪問するほど有名な史の場所になっている。現在はを中心として大型金融施設、商業施設などがあり、交通需要が多くある。近隣の療機は錦南路5街5番出口を出て、デシン券方面に道を渡って３番出口方面に80ｍ以マルグンモリキムドンウク神院がある。4721_금남로5가역_5_의료기관_001
1464공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_송정공원역_4_중국어_316.mp311641송정공원역316松汀公站光州主要公共汽点站之一的道山洞，因此附近市公共汽班偏多。松汀公的金仙寺，魂碑，李起巽迹碑，朴喆碑令人回起烈的史。站部的光州地文里以形式展示着全南道人朴喆，茶兄金承，李福，金永郞的作品。附近的公共机광주소프트웨어 마이스터고등학교。位于1口右。12631_송정공원역_4_공공기관_001
1465공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_농성역_6_일본어_176.mp310961농성역176農城は1番出口がガラス屋根の場になっていて地下2層まで日光がたる。周りに光州合バスタミナル、ギアチャンピオンズフィルドと大型書店など大きい施設があり、文化や余暇をしむことができ、祭りとして有名で利用客が多い。近隣の公共機はヨンサンガン洪水管理センタであり、6番出口でチュクポン大路22番ギルに移動して約200m直進すれば前にある。7041_농성역_6_공공기관_001
1466의료기관https://openapi.grtc.co.kr/upload/brand/voice/1_금남로5가역_2_일본어_106.mp310621금남로5가역106錦南路5街は地下2階に光州生立運動の資料や映ポスタなどが整っている空間が造成されており、多くの著名人が訪問するほど有名な史の場所になっている。現在はを中心として大型金融施設、商業施設などがあり、交通需要が多くある。錦南路5街2番出口を出て、100m以マルグンモリキムドンウク神院がある。4241_금남로5가역_2_의료기관_001
1467공공기관https://openapi.grtc.co.kr/upload/brand/voice/1_금남로4가역_1_중국어_085.mp310511금남로4가역85南路4街站名于的地下商街。此的表演和志愿服活吸引着男女老少。且，因此站位于光州具代表性的繁街附近，南路4街站是光州地站中乘客最多的站。附近的公共机광주세무서。1口向西南方向步行360米可到目的地。3391_금남로4가역_1_공공기관_002