Overview

Dataset statistics

Number of variables39
Number of observations4134
Missing cells74360
Missing cells (%)46.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory335.0 B

Variable types

Numeric23
Categorical8
Text8

Dataset

Description2022년도 수출기업 글로벌역량진단 사업 DB (수출의지, 기초자원, 인프라 등) 및 기업정보 (수출품목, 수출액 등) 정보를 제공
Author대한무역투자진흥공사
URLhttps://www.data.go.kr/data/15091605/fileData.do

Alerts

내수용기업유형1 is highly imbalanced (70.1%)Imbalance
수출용기업유형1 is highly imbalanced (72.6%)Imbalance
수출용기업유형2 is highly imbalanced (58.8%)Imbalance
수출용주소 is highly imbalanced (61.3%)Imbalance
내수용총점 has 1062 (25.7%) missing valuesMissing
내수용수출의지 has 1062 (25.7%) missing valuesMissing
내수용기초자원 has 1062 (25.7%) missing valuesMissing
내수용수출인프라 has 1062 (25.7%) missing valuesMissing
내수용마케팅네트워크 has 1062 (25.7%) missing valuesMissing
내수용수출제품코드 has 1062 (25.7%) missing valuesMissing
내수용수출제품명 has 1231 (29.8%) missing valuesMissing
내수용주요수출국가1 has 1426 (34.5%) missing valuesMissing
내수용주요수출국가2 has 1512 (36.6%) missing valuesMissing
내수용주요수출국가3 has 1659 (40.1%) missing valuesMissing
수출용총점 has 3072 (74.3%) missing valuesMissing
수출용수출실적 has 3072 (74.3%) missing valuesMissing
수출용준비점수 has 3072 (74.3%) missing valuesMissing
수출용활용점수 has 3072 (74.3%) missing valuesMissing
수출용심화점수 has 3072 (74.3%) missing valuesMissing
수출용비전마인드 has 3072 (74.3%) missing valuesMissing
수출용인프라 has 3072 (74.3%) missing valuesMissing
수출용인력및자금 has 3072 (74.3%) missing valuesMissing
수출용의사소통 has 3072 (74.3%) missing valuesMissing
수출용판촉온라인 has 3072 (74.3%) missing valuesMissing
수출용네트워크 has 3072 (74.3%) missing valuesMissing
수출용시장전략 has 3072 (74.3%) missing valuesMissing
수출용제품 has 3072 (74.3%) missing valuesMissing
수출용매출금액 has 3072 (74.3%) missing valuesMissing
수출용수출금액 has 3072 (74.3%) missing valuesMissing
수출용수출제품코드 has 3072 (74.3%) missing valuesMissing
수출용수출제품명 has 3112 (75.3%) missing valuesMissing
수출용주요수출국가1 has 3252 (78.7%) missing valuesMissing
수출용주요수출국가2 has 3291 (79.6%) missing valuesMissing
수출용주요수출국가3 has 3353 (81.1%) missing valuesMissing
수출용매출금액 is highly skewed (γ1 = 32.28246511)Skewed
수출용수출금액 is highly skewed (γ1 = 30.797762)Skewed
번호 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:01:35.864531
Analysis finished2024-04-21 02:01:37.985760
Duration2.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct4134
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2067.5
Minimum1
Maximum4134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:38.071474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile207.65
Q11034.25
median2067.5
Q33100.75
95-th percentile3927.35
Maximum4134
Range4133
Interquartile range (IQR)2066.5

Descriptive statistics

Standard deviation1193.5273
Coefficient of variation (CV)0.57728045
Kurtosis-1.2
Mean2067.5
Median Absolute Deviation (MAD)1033.5
Skewness0
Sum8547045
Variance1424507.5
MonotonicityStrictly increasing
2024-04-21T11:01:38.192585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2779 1
 
< 0.1%
2749 1
 
< 0.1%
2750 1
 
< 0.1%
2751 1
 
< 0.1%
2752 1
 
< 0.1%
2753 1
 
< 0.1%
2754 1
 
< 0.1%
2755 1
 
< 0.1%
2756 1
 
< 0.1%
Other values (4124) 4124
99.8%
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 (%)
4134 1
< 0.1%
4133 1
< 0.1%
4132 1
< 0.1%
4131 1
< 0.1%
4130 1
< 0.1%
4129 1
< 0.1%
4128 1
< 0.1%
4127 1
< 0.1%
4126 1
< 0.1%
4125 1
< 0.1%

내수용기업유형1
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
중소기업
3040 
<NA>
1062 
중견기업
 
21
중소기업,중견기업
 
4
극내 대기업 계열사
 
3
Other values (3)
 
4

Length

Max length10
Median length4
Mean length4.0104015
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row중소기업
2nd row중견기업
3rd row중소기업
4th row중소기업
5th row중소기업

Common Values

ValueCountFrequency (%)
중소기업 3040
73.5%
<NA> 1062
 
25.7%
중견기업 21
 
0.5%
중소기업,중견기업 4
 
0.1%
극내 대기업 계열사 3
 
0.1%
대기업 2
 
< 0.1%
중소기업,외국계기업 1
 
< 0.1%
외국계기업 1
 
< 0.1%

Length

2024-04-21T11:01:38.319719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:01:38.448097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중소기업 3040
73.4%
na 1062
 
25.7%
중견기업 21
 
0.5%
대기업 5
 
0.1%
중소기업,중견기업 4
 
0.1%
극내 3
 
0.1%
계열사 3
 
0.1%
중소기업,외국계기업 1
 
< 0.1%
외국계기업 1
 
< 0.1%

내수용기업유형2
Categorical

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
제조기업
2194 
<NA>
1062 
수출중개기업(오퍼상,에이전트 등)
261 
서비스기업
235 
제조기업,서비스기업
 
215
Other values (3)
 
167

Length

Max length29
Median length4
Mean length6.0650701
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제조기업
2nd row제조기업
3rd row제조기업
4th row제조기업
5th row제조기업,서비스기업

Common Values

ValueCountFrequency (%)
제조기업 2194
53.1%
<NA> 1062
25.7%
수출중개기업(오퍼상,에이전트 등) 261
 
6.3%
서비스기업 235
 
5.7%
제조기업,서비스기업 215
 
5.2%
제조기업,수출중개기업(오퍼상,에이전트 등) 92
 
2.2%
서비스기업,수출중개기업(오퍼상,에이전트 등) 53
 
1.3%
제조기업,서비스기업,수출중개기업(오퍼상,에이전트 등) 22
 
0.5%

Length

2024-04-21T11:01:38.599947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:01:38.739984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제조기업 2194
48.1%
na 1062
23.3%
등 428
 
9.4%
수출중개기업(오퍼상,에이전트 261
 
5.7%
서비스기업 235
 
5.2%
제조기업,서비스기업 215
 
4.7%
제조기업,수출중개기업(오퍼상,에이전트 92
 
2.0%
서비스기업,수출중개기업(오퍼상,에이전트 53
 
1.2%
제조기업,서비스기업,수출중개기업(오퍼상,에이전트 22
 
0.5%

내수용역량등급
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
성장내수기업
1743 
<NA>
1062 
초보내수기업
956 
유망내수기업
373 

Length

Max length6
Median length6
Mean length5.4862119
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성장내수기업 1743
42.2%
<NA> 1062
25.7%
초보내수기업 956
23.1%
유망내수기업 373
 
9.0%

Length

2024-04-21T11:01:38.897634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:01:39.032344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성장내수기업 1743
42.2%
na 1062
25.7%
초보내수기업 956
23.1%
유망내수기업 373
 
9.0%

내수용주소
Categorical

Distinct19
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
1062 
경기
789 
서울
769 
부산
215 
경북
193 
Other values (14)
1106 

Length

Max length4
Median length2
Mean length2.5174165
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기
2nd row서울
3rd row경기
4th row경남
5th row서울

Common Values

ValueCountFrequency (%)
<NA> 1062
25.7%
경기 789
19.1%
서울 769
18.6%
부산 215
 
5.2%
경북 193
 
4.7%
경남 177
 
4.3%
대구 131
 
3.2%
인천 126
 
3.0%
대전 108
 
2.6%
전북 93
 
2.2%
Other values (9) 471
11.4%

Length

2024-04-21T11:01:39.160305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1062
25.7%
경기 789
19.1%
서울 769
18.6%
부산 215
 
5.2%
경북 193
 
4.7%
경남 177
 
4.3%
대구 131
 
3.2%
인천 126
 
3.0%
대전 108
 
2.6%
전북 93
 
2.2%
Other values (9) 471
11.4%

내수용총점
Real number (ℝ)

MISSING 

Distinct556
Distinct (%)18.1%
Missing1062
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean65.922301
Minimum25.67
Maximum99.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:39.310658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.67
5-th percentile46.42
Q157.92
median65.92
Q374.08
95-th percentile85.5
Maximum99.5
Range73.83
Interquartile range (IQR)16.16

Descriptive statistics

Standard deviation11.773434
Coefficient of variation (CV)0.17859562
Kurtosis-0.16163227
Mean65.922301
Median Absolute Deviation (MAD)8.16
Skewness-0.0097316775
Sum202513.31
Variance138.61375
MonotonicityNot monotonic
2024-04-21T11:01:39.449409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64.92 20
 
0.5%
60.42 19
 
0.5%
65.17 18
 
0.4%
63.92 18
 
0.4%
66.17 18
 
0.4%
59.17 18
 
0.4%
71.75 17
 
0.4%
62.67 17
 
0.4%
67.58 16
 
0.4%
68.58 16
 
0.4%
Other values (546) 2895
70.0%
(Missing) 1062
 
25.7%
ValueCountFrequency (%)
25.67 2
< 0.1%
26.17 1
< 0.1%
27.17 1
< 0.1%
29.67 1
< 0.1%
32.67 1
< 0.1%
34.17 2
< 0.1%
35.67 2
< 0.1%
35.83 2
< 0.1%
35.92 1
< 0.1%
36.08 1
< 0.1%
ValueCountFrequency (%)
99.5 1
 
< 0.1%
99.0 2
< 0.1%
98.5 3
0.1%
98.0 1
 
< 0.1%
97.5 2
< 0.1%
97.17 1
 
< 0.1%
97.0 3
0.1%
96.92 1
 
< 0.1%
96.83 1
 
< 0.1%
96.0 3
0.1%

내수용수출의지
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)2.4%
Missing1062
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean21.304688
Minimum7.5
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:39.591125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.5
5-th percentile14.5
Q118.75
median21.75
Q324.25
95-th percentile27.25
Maximum30
Range22.5
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.9276493
Coefficient of variation (CV)0.18435611
Kurtosis-0.23912927
Mean21.304688
Median Absolute Deviation (MAD)2.5
Skewness-0.38470412
Sum65448
Variance15.426429
MonotonicityNot monotonic
2024-04-21T11:01:39.817086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.25 128
 
3.1%
25.0 113
 
2.7%
24.25 106
 
2.6%
19.25 102
 
2.5%
24.0 101
 
2.4%
21.0 98
 
2.4%
23.0 93
 
2.2%
20.25 91
 
2.2%
21.25 87
 
2.1%
22.25 85
 
2.1%
Other values (64) 2068
50.0%
(Missing) 1062
25.7%
ValueCountFrequency (%)
7.5 4
 
0.1%
9.5 4
 
0.1%
10.25 1
 
< 0.1%
10.5 10
0.2%
11.25 6
 
0.1%
11.5 10
0.2%
12.25 7
 
0.2%
12.5 21
0.5%
12.75 1
 
< 0.1%
13.0 2
 
< 0.1%
ValueCountFrequency (%)
30.0 15
 
0.4%
29.25 11
 
0.3%
29.0 12
 
0.3%
28.5 25
0.6%
28.25 14
 
0.3%
28.0 3
 
0.1%
27.75 21
0.5%
27.5 41
1.0%
27.25 16
 
0.4%
27.0 18
0.4%

내수용기초자원
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)1.0%
Missing1062
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean14.574056
Minimum5
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:39.987623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile11
Q113
median14.5
Q316
95-th percentile18
Maximum20
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.1395397
Coefficient of variation (CV)0.14680469
Kurtosis0.31646762
Mean14.574056
Median Absolute Deviation (MAD)1.5
Skewness-0.19662373
Sum44771.5
Variance4.5776302
MonotonicityNot monotonic
2024-04-21T11:01:40.147048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
14.5 299
 
7.2%
14.0 284
 
6.9%
15.0 281
 
6.8%
13.5 269
 
6.5%
16.0 256
 
6.2%
15.5 243
 
5.9%
13.0 203
 
4.9%
16.5 194
 
4.7%
12.5 165
 
4.0%
17.0 134
 
3.2%
Other values (20) 744
18.0%
(Missing) 1062
25.7%
ValueCountFrequency (%)
5.0 2
 
< 0.1%
5.5 1
 
< 0.1%
6.0 1
 
< 0.1%
6.5 2
 
< 0.1%
7.5 3
 
0.1%
8.0 3
 
0.1%
8.5 8
 
0.2%
9.0 6
 
0.1%
9.5 17
0.4%
10.0 29
0.7%
ValueCountFrequency (%)
20.0 13
 
0.3%
19.5 15
 
0.4%
19.0 47
 
1.1%
18.5 63
 
1.5%
18.0 67
 
1.6%
17.5 123
3.0%
17.0 134
3.2%
16.5 194
4.7%
16.0 256
6.2%
15.5 243
5.9%

내수용수출인프라
Real number (ℝ)

MISSING 

Distinct77
Distinct (%)2.5%
Missing1062
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean12.372497
Minimum5.67
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:40.314571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.67
5-th percentile7.17
Q110.17
median12.33
Q314.5
95-th percentile17.5
Maximum20
Range14.33
Interquartile range (IQR)4.33

Descriptive statistics

Standard deviation3.0582188
Coefficient of variation (CV)0.24717879
Kurtosis-0.47201228
Mean12.372497
Median Absolute Deviation (MAD)2.16
Skewness0.072755386
Sum38008.31
Variance9.3527022
MonotonicityNot monotonic
2024-04-21T11:01:40.536237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.17 119
 
2.9%
11.17 111
 
2.7%
9.17 99
 
2.4%
11.67 95
 
2.3%
10.67 94
 
2.3%
8.67 89
 
2.2%
12.17 88
 
2.1%
11.83 84
 
2.0%
13.33 83
 
2.0%
9.67 83
 
2.0%
Other values (67) 2127
51.5%
(Missing) 1062
25.7%
ValueCountFrequency (%)
5.67 42
1.0%
6.17 27
0.7%
6.33 2
 
< 0.1%
6.67 29
0.7%
6.83 2
 
< 0.1%
7.17 66
1.6%
7.33 8
 
0.2%
7.67 45
1.1%
7.83 7
 
0.2%
8.0 1
 
< 0.1%
ValueCountFrequency (%)
20.0 20
0.5%
19.5 16
0.4%
19.33 2
 
< 0.1%
19.0 10
 
0.2%
18.83 4
 
0.1%
18.5 26
0.6%
18.33 4
 
0.1%
18.17 2
 
< 0.1%
18.0 34
0.8%
17.83 15
0.4%

내수용마케팅네트워크
Real number (ℝ)

MISSING 

Distinct46
Distinct (%)1.5%
Missing1062
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean17.671061
Minimum7.5
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:40.727171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.5
5-th percentile10.5
Q114.5
median17.5
Q320.5
95-th percentile25.5
Maximum30
Range22.5
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.4544936
Coefficient of variation (CV)0.25207844
Kurtosis-0.31109409
Mean17.671061
Median Absolute Deviation (MAD)3
Skewness0.23424315
Sum54285.5
Variance19.842513
MonotonicityNot monotonic
2024-04-21T11:01:40.904200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
18.0 156
 
3.8%
15.5 144
 
3.5%
16.5 144
 
3.5%
12.5 129
 
3.1%
16.0 129
 
3.1%
19.0 125
 
3.0%
14.5 125
 
3.0%
17.0 125
 
3.0%
18.5 123
 
3.0%
20.0 123
 
3.0%
Other values (36) 1749
42.3%
(Missing) 1062
25.7%
ValueCountFrequency (%)
7.5 20
 
0.5%
8.0 2
 
< 0.1%
8.5 16
 
0.4%
9.0 7
 
0.2%
9.5 47
1.1%
10.0 7
 
0.2%
10.5 67
1.6%
11.0 23
 
0.6%
11.5 100
2.4%
12.0 36
 
0.9%
ValueCountFrequency (%)
30.0 18
0.4%
29.5 2
 
< 0.1%
29.0 6
 
0.1%
28.5 10
 
0.2%
28.0 20
0.5%
27.5 10
 
0.2%
27.0 23
0.6%
26.5 10
 
0.2%
26.0 40
1.0%
25.5 21
0.5%

내수용수출제품코드
Real number (ℝ)

MISSING 

Distinct361
Distinct (%)11.8%
Missing1062
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean4864.6413
Minimum111
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:41.082475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111
5-th percentile159
Q12275
median5161
Q37901
95-th percentile9900
Maximum9999
Range9888
Interquartile range (IQR)5626

Descriptive statistics

Standard deviation3260.1444
Coefficient of variation (CV)0.67017159
Kurtosis-1.3322613
Mean4864.6413
Median Absolute Deviation (MAD)2886
Skewness-0.0065580351
Sum14944178
Variance10628541
MonotonicityNot monotonic
2024-04-21T11:01:41.238672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2275 401
 
9.7%
169 172
 
4.2%
9900 134
 
3.2%
5900 129
 
3.1%
7331 88
 
2.1%
3109 70
 
1.7%
9999 58
 
1.4%
9509 49
 
1.2%
4412 48
 
1.2%
4490 47
 
1.1%
Other values (351) 1876
45.4%
(Missing) 1062
25.7%
ValueCountFrequency (%)
111 8
0.2%
113 2
 
< 0.1%
114 1
 
< 0.1%
116 4
0.1%
119 5
0.1%
121 3
 
0.1%
123 1
 
< 0.1%
124 7
0.2%
125 1
 
< 0.1%
131 4
0.1%
ValueCountFrequency (%)
9999 58
1.4%
9996 9
 
0.2%
9995 2
 
< 0.1%
9993 12
 
0.3%
9991 2
 
< 0.1%
9926 10
 
0.2%
9925 4
 
0.1%
9922 3
 
0.1%
9921 1
 
< 0.1%
9900 134
3.2%

내수용수출제품명
Text

MISSING 

Distinct334
Distinct (%)11.5%
Missing1231
Missing (%)29.8%
Memory size32.4 KiB
2024-04-21T11:01:41.564870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length15
Mean length4.9038925
Min length1

Characters and Unicode

Total characters14236
Distinct characters304
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)3.8%

Sample

1st row계측기
2nd row기타취미오락용구
3rd row기타조명기기
4th row의료용기기
5th row식품포장기계
ValueCountFrequency (%)
화장품 401
 
13.6%
기타농산가공품 172
 
5.8%
기타잡제품 134
 
4.6%
기타생활용품 129
 
4.4%
의료용기기 88
 
3.0%
기타플라스틱제품 70
 
2.4%
기타서비스 58
 
2.0%
기타의료위생용품 49
 
1.7%
직물제의류 48
 
1.6%
기타섬유제품 47
 
1.6%
Other values (334) 1747
59.4%
2024-04-21T11:01:42.322964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1907
 
13.4%
품 1394
 
9.8%
타 1279
 
9.0%
제 487
 
3.4%
장 441
 
3.1%
화 440
 
3.1%
용 427
 
3.0%
가 380
 
2.7%
류 323
 
2.3%
공 323
 
2.3%
Other values (294) 6835
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14039
98.6%
Lowercase Letter 133
 
0.9%
Space Separator 40
 
0.3%
Close Punctuation 10
 
0.1%
Open Punctuation 10
 
0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1907
 
13.6%
품 1394
 
9.9%
타 1279
 
9.1%
제 487
 
3.5%
장 441
 
3.1%
화 440
 
3.1%
용 427
 
3.0%
가 380
 
2.7%
류 323
 
2.3%
공 323
 
2.3%
Other values (278) 6638
47.3%
Lowercase Letter
ValueCountFrequency (%)
e 27
20.3%
c 20
15.0%
r 16
12.0%
t 13
9.8%
i 10
 
7.5%
l 10
 
7.5%
y 10
 
7.5%
a 10
 
7.5%
h 7
 
5.3%
v 7
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
V 2
50.0%
T 2
50.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14039
98.6%
Latin 137
 
1.0%
Common 60
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1907
 
13.6%
품 1394
 
9.9%
타 1279
 
9.1%
제 487
 
3.5%
장 441
 
3.1%
화 440
 
3.1%
용 427
 
3.0%
가 380
 
2.7%
류 323
 
2.3%
공 323
 
2.3%
Other values (278) 6638
47.3%
Latin
ValueCountFrequency (%)
e 27
19.7%
c 20
14.6%
r 16
11.7%
t 13
9.5%
i 10
 
7.3%
l 10
 
7.3%
y 10
 
7.3%
a 10
 
7.3%
h 7
 
5.1%
v 7
 
5.1%
Other values (3) 7
 
5.1%
Common
ValueCountFrequency (%)
40
66.7%
) 10
 
16.7%
( 10
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14039
98.6%
ASCII 197
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1907
 
13.6%
품 1394
 
9.9%
타 1279
 
9.1%
제 487
 
3.5%
장 441
 
3.1%
화 440
 
3.1%
용 427
 
3.0%
가 380
 
2.7%
류 323
 
2.3%
공 323
 
2.3%
Other values (278) 6638
47.3%
ASCII
ValueCountFrequency (%)
40
20.3%
e 27
13.7%
c 20
10.2%
r 16
 
8.1%
t 13
 
6.6%
) 10
 
5.1%
i 10
 
5.1%
l 10
 
5.1%
y 10
 
5.1%
a 10
 
5.1%
Other values (6) 31
15.7%

내수용주요수출국가1
Text

MISSING 

Distinct359
Distinct (%)13.3%
Missing1426
Missing (%)34.5%
Memory size32.4 KiB
2024-04-21T11:01:42.515703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length2
Mean length2.8711226
Min length1

Characters and Unicode

Total characters7775
Distinct characters436
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique287 ?
Unique (%)10.6%

Sample

1st row베트남
2nd row유럽
3rd row아르헨티나
4th row미국
5th rowㅁ
ValueCountFrequency (%)
미국 753
26.2%
중국 342
11.9%
일본 315
 
11.0%
베트남 160
 
5.6%
유럽 122
 
4.2%
동남아 106
 
3.7%
북미 102
 
3.6%
동남아시아 74
 
2.6%
러시아 45
 
1.6%
인도네시아 36
 
1.3%
Other values (423) 817
28.4%
2024-04-21T11:01:42.915019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 1150
 
14.8%
미 923
 
11.9%
아 455
 
5.9%
중 392
 
5.0%
남 362
 
4.7%
일 344
 
4.4%
본 317
 
4.1%
동 237
 
3.0%
시 216
 
2.8%
215
 
2.8%
Other values (426) 3164
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7197
92.6%
Space Separator 215
 
2.8%
Uppercase Letter 136
 
1.7%
Lowercase Letter 116
 
1.5%
Other Punctuation 33
 
0.4%
Close Punctuation 30
 
0.4%
Open Punctuation 30
 
0.4%
Decimal Number 13
 
0.2%
Dash Punctuation 4
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 1150
16.0%
미 923
 
12.8%
아 455
 
6.3%
중 392
 
5.4%
남 362
 
5.0%
일 344
 
4.8%
본 317
 
4.4%
동 237
 
3.3%
시 216
 
3.0%
트 191
 
2.7%
Other values (370) 2610
36.3%
Uppercase Letter
ValueCountFrequency (%)
E 22
16.2%
U 21
15.4%
I 16
11.8%
A 15
11.0%
S 14
10.3%
C 9
6.6%
D 8
 
5.9%
B 5
 
3.7%
L 5
 
3.7%
T 4
 
2.9%
Other values (10) 17
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 14
12.1%
a 13
11.2%
t 13
11.2%
r 12
10.3%
o 12
10.3%
s 7
 
6.0%
i 7
 
6.0%
u 6
 
5.2%
c 5
 
4.3%
p 5
 
4.3%
Other values (9) 22
19.0%
Decimal Number
ValueCountFrequency (%)
0 4
30.8%
7 2
15.4%
4 2
15.4%
3 2
15.4%
9 1
 
7.7%
1 1
 
7.7%
2 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 29
87.9%
; 1
 
3.0%
. 1
 
3.0%
& 1
 
3.0%
/ 1
 
3.0%
Space Separator
ValueCountFrequency (%)
215
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7197
92.6%
Common 326
 
4.2%
Latin 252
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 1150
16.0%
미 923
 
12.8%
아 455
 
6.3%
중 392
 
5.4%
남 362
 
5.0%
일 344
 
4.8%
본 317
 
4.4%
동 237
 
3.3%
시 216
 
3.0%
트 191
 
2.7%
Other values (370) 2610
36.3%
Latin
ValueCountFrequency (%)
E 22
 
8.7%
U 21
 
8.3%
I 16
 
6.3%
A 15
 
6.0%
S 14
 
5.6%
e 14
 
5.6%
a 13
 
5.2%
t 13
 
5.2%
r 12
 
4.8%
o 12
 
4.8%
Other values (29) 100
39.7%
Common
ValueCountFrequency (%)
215
66.0%
) 30
 
9.2%
( 30
 
9.2%
, 29
 
8.9%
- 4
 
1.2%
0 4
 
1.2%
7 2
 
0.6%
4 2
 
0.6%
3 2
 
0.6%
_ 1
 
0.3%
Other values (7) 7
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7196
92.6%
ASCII 578
 
7.4%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 1150
16.0%
미 923
 
12.8%
아 455
 
6.3%
중 392
 
5.4%
남 362
 
5.0%
일 344
 
4.8%
본 317
 
4.4%
동 237
 
3.3%
시 216
 
3.0%
트 191
 
2.7%
Other values (369) 2609
36.3%
ASCII
ValueCountFrequency (%)
215
37.2%
) 30
 
5.2%
( 30
 
5.2%
, 29
 
5.0%
E 22
 
3.8%
U 21
 
3.6%
I 16
 
2.8%
A 15
 
2.6%
S 14
 
2.4%
e 14
 
2.4%
Other values (46) 172
29.8%
Compat Jamo
ValueCountFrequency (%)
ㅁ 1
100.0%

내수용주요수출국가2
Text

MISSING 

Distinct341
Distinct (%)13.0%
Missing1512
Missing (%)36.6%
Memory size32.4 KiB
2024-04-21T11:01:43.167868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length2
Mean length2.9191457
Min length2

Characters and Unicode

Total characters7654
Distinct characters384
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique269 ?
Unique (%)10.3%

Sample

1st row인도
2nd row동남아시아
3rd row뉴질랜드
4th rowEU
5th row베트남
ValueCountFrequency (%)
일본 331
 
12.1%
중국 310
 
11.3%
미국 308
 
11.2%
유럽 291
 
10.6%
베트남 166
 
6.0%
동남아 108
 
3.9%
동남아시아 74
 
2.7%
중동 63
 
2.3%
북미 60
 
2.2%
러시아 57
 
2.1%
Other values (380) 978
35.6%
2024-04-21T11:01:43.571104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 688
 
9.0%
아 523
 
6.8%
미 438
 
5.7%
남 406
 
5.3%
중 402
 
5.3%
일 369
 
4.8%
본 335
 
4.4%
유 311
 
4.1%
럽 307
 
4.0%
동 271
 
3.5%
Other values (374) 3604
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7091
92.6%
Space Separator 175
 
2.3%
Uppercase Letter 170
 
2.2%
Lowercase Letter 153
 
2.0%
Other Punctuation 20
 
0.3%
Close Punctuation 19
 
0.2%
Open Punctuation 19
 
0.2%
Dash Punctuation 4
 
0.1%
Decimal Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 688
 
9.7%
아 523
 
7.4%
미 438
 
6.2%
남 406
 
5.7%
중 402
 
5.7%
일 369
 
5.2%
본 335
 
4.7%
유 311
 
4.4%
럽 307
 
4.3%
동 271
 
3.8%
Other values (323) 3041
42.9%
Lowercase Letter
ValueCountFrequency (%)
e 18
11.8%
o 18
11.8%
r 15
9.8%
n 14
9.2%
a 13
8.5%
i 13
8.5%
t 9
 
5.9%
m 8
 
5.2%
p 7
 
4.6%
s 7
 
4.6%
Other values (11) 31
20.3%
Uppercase Letter
ValueCountFrequency (%)
E 39
22.9%
U 31
18.2%
A 18
10.6%
S 15
 
8.8%
C 11
 
6.5%
I 11
 
6.5%
N 7
 
4.1%
L 6
 
3.5%
T 5
 
2.9%
P 5
 
2.9%
Other values (10) 22
12.9%
Other Punctuation
ValueCountFrequency (%)
, 16
80.0%
. 2
 
10.0%
/ 2
 
10.0%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
1 1
33.3%
6 1
33.3%
Space Separator
ValueCountFrequency (%)
175
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7091
92.6%
Latin 323
 
4.2%
Common 240
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 688
 
9.7%
아 523
 
7.4%
미 438
 
6.2%
남 406
 
5.7%
중 402
 
5.7%
일 369
 
5.2%
본 335
 
4.7%
유 311
 
4.4%
럽 307
 
4.3%
동 271
 
3.8%
Other values (323) 3041
42.9%
Latin
ValueCountFrequency (%)
E 39
 
12.1%
U 31
 
9.6%
e 18
 
5.6%
o 18
 
5.6%
A 18
 
5.6%
r 15
 
4.6%
S 15
 
4.6%
n 14
 
4.3%
a 13
 
4.0%
i 13
 
4.0%
Other values (31) 129
39.9%
Common
ValueCountFrequency (%)
175
72.9%
) 19
 
7.9%
( 19
 
7.9%
, 16
 
6.7%
- 4
 
1.7%
. 2
 
0.8%
/ 2
 
0.8%
2 1
 
0.4%
1 1
 
0.4%
6 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7091
92.6%
ASCII 563
 
7.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 688
 
9.7%
아 523
 
7.4%
미 438
 
6.2%
남 406
 
5.7%
중 402
 
5.7%
일 369
 
5.2%
본 335
 
4.7%
유 311
 
4.4%
럽 307
 
4.3%
동 271
 
3.8%
Other values (323) 3041
42.9%
ASCII
ValueCountFrequency (%)
175
31.1%
E 39
 
6.9%
U 31
 
5.5%
) 19
 
3.4%
( 19
 
3.4%
e 18
 
3.2%
o 18
 
3.2%
A 18
 
3.2%
, 16
 
2.8%
r 15
 
2.7%
Other values (41) 195
34.6%

내수용주요수출국가3
Text

MISSING 

Distinct309
Distinct (%)12.5%
Missing1659
Missing (%)40.1%
Memory size32.4 KiB
2024-04-21T11:01:43.884006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length2
Mean length2.9527273
Min length2

Characters and Unicode

Total characters7308
Distinct characters337
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique231 ?
Unique (%)9.3%

Sample

1st row인도네시아
2nd row북아메리카
3rd row유럽
4th row중동
5th row미국
ValueCountFrequency (%)
일본 267
 
10.3%
유럽 250
 
9.7%
중국 242
 
9.4%
미국 199
 
7.7%
동남아 141
 
5.5%
베트남 133
 
5.2%
중동 101
 
3.9%
러시아 77
 
3.0%
동남아시아 74
 
2.9%
인도네시아 57
 
2.2%
Other values (323) 1041
40.3%
2024-04-21T11:01:44.342272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 715
 
9.8%
국 521
 
7.1%
남 434
 
5.9%
중 381
 
5.2%
시 355
 
4.9%
동 331
 
4.5%
미 331
 
4.5%
일 307
 
4.2%
본 274
 
3.7%
유 265
 
3.6%
Other values (327) 3394
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6898
94.4%
Space Separator 139
 
1.9%
Uppercase Letter 111
 
1.5%
Lowercase Letter 96
 
1.3%
Other Punctuation 25
 
0.3%
Close Punctuation 13
 
0.2%
Open Punctuation 13
 
0.2%
Dash Punctuation 6
 
0.1%
Decimal Number 6
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 715
 
10.4%
국 521
 
7.6%
남 434
 
6.3%
중 381
 
5.5%
시 355
 
5.1%
동 331
 
4.8%
미 331
 
4.8%
일 307
 
4.5%
본 274
 
4.0%
유 265
 
3.8%
Other values (281) 2984
43.3%
Lowercase Letter
ValueCountFrequency (%)
a 14
14.6%
i 12
12.5%
s 11
11.5%
n 9
9.4%
e 9
9.4%
p 6
 
6.2%
o 6
 
6.2%
d 5
 
5.2%
r 5
 
5.2%
l 4
 
4.2%
Other values (8) 15
15.6%
Uppercase Letter
ValueCountFrequency (%)
E 23
20.7%
U 20
18.0%
C 13
11.7%
S 13
11.7%
A 11
9.9%
I 11
9.9%
L 5
 
4.5%
R 4
 
3.6%
D 2
 
1.8%
T 2
 
1.8%
Other values (7) 7
 
6.3%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
2 2
33.3%
0 1
16.7%
7 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 20
80.0%
/ 5
 
20.0%
Space Separator
ValueCountFrequency (%)
139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6898
94.4%
Latin 207
 
2.8%
Common 203
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 715
 
10.4%
국 521
 
7.6%
남 434
 
6.3%
중 381
 
5.5%
시 355
 
5.1%
동 331
 
4.8%
미 331
 
4.8%
일 307
 
4.5%
본 274
 
4.0%
유 265
 
3.8%
Other values (281) 2984
43.3%
Latin
ValueCountFrequency (%)
E 23
 
11.1%
U 20
 
9.7%
a 14
 
6.8%
C 13
 
6.3%
S 13
 
6.3%
i 12
 
5.8%
s 11
 
5.3%
A 11
 
5.3%
I 11
 
5.3%
n 9
 
4.3%
Other values (25) 70
33.8%
Common
ValueCountFrequency (%)
139
68.5%
, 20
 
9.9%
) 13
 
6.4%
( 13
 
6.4%
- 6
 
3.0%
/ 5
 
2.5%
1 2
 
1.0%
2 2
 
1.0%
+ 1
 
0.5%
0 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6897
94.4%
ASCII 410
 
5.6%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 715
 
10.4%
국 521
 
7.6%
남 434
 
6.3%
중 381
 
5.5%
시 355
 
5.1%
동 331
 
4.8%
미 331
 
4.8%
일 307
 
4.5%
본 274
 
4.0%
유 265
 
3.8%
Other values (280) 2983
43.3%
ASCII
ValueCountFrequency (%)
139
33.9%
E 23
 
5.6%
, 20
 
4.9%
U 20
 
4.9%
a 14
 
3.4%
) 13
 
3.2%
( 13
 
3.2%
C 13
 
3.2%
S 13
 
3.2%
i 12
 
2.9%
Other values (36) 130
31.7%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

수출용기업유형1
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
3072 
중소기업
986 
중견기업
 
51
대기업
 
10
극내 대기업 계열사
 
5
Other values (6)
 
10

Length

Max length15
Median length4
Mean length4.0205612
Min length3

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3072
74.3%
중소기업 986
 
23.9%
중견기업 51
 
1.2%
대기업 10
 
0.2%
극내 대기업 계열사 5
 
0.1%
중소기업,중견기업 4
 
0.1%
중소기업,외국계기업 2
 
< 0.1%
대기업,극내 대기업 계열사 1
 
< 0.1%
외국계기업 1
 
< 0.1%
중소기업,중견기업,외국계기업 1
 
< 0.1%

Length

2024-04-21T11:01:44.476972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3072
74.1%
중소기업 986
 
23.8%
중견기업 51
 
1.2%
대기업 17
 
0.4%
계열사 7
 
0.2%
극내 5
 
0.1%
중소기업,중견기업 4
 
0.1%
중소기업,외국계기업 2
 
< 0.1%
대기업,극내 1
 
< 0.1%
외국계기업 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

수출용기업유형2
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
3072 
제조기업
734 
수출중개기업(오퍼상,에이전트 등)
 
113
제조기업,서비스기업
 
75
제조기업,수출중개기업(오퍼상,에이전트 등)
 
54
Other values (3)
 
86

Length

Max length29
Median length4
Mean length4.967344
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3072
74.3%
제조기업 734
 
17.8%
수출중개기업(오퍼상,에이전트 등) 113
 
2.7%
제조기업,서비스기업 75
 
1.8%
제조기업,수출중개기업(오퍼상,에이전트 등) 54
 
1.3%
서비스기업 46
 
1.1%
서비스기업,수출중개기업(오퍼상,에이전트 등) 21
 
0.5%
제조기업,서비스기업,수출중개기업(오퍼상,에이전트 등) 19
 
0.5%

Length

2024-04-21T11:01:44.596490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:01:44.728419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3072
70.8%
제조기업 734
 
16.9%
등 207
 
4.8%
수출중개기업(오퍼상,에이전트 113
 
2.6%
제조기업,서비스기업 75
 
1.7%
제조기업,수출중개기업(오퍼상,에이전트 54
 
1.2%
서비스기업 46
 
1.1%
서비스기업,수출중개기업(오퍼상,에이전트 21
 
0.5%
제조기업,서비스기업,수출중개기업(오퍼상,에이전트 19
 
0.4%

수출용역량등급
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
3072 
글로벌 유망기업
596 
글로벌 초보기업
 
228
글로벌 선도기업
 
164
글로벌 강소기업
 
74

Length

Max length8
Median length4
Mean length5.0275762
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3072
74.3%
글로벌 유망기업 596
 
14.4%
글로벌 초보기업 228
 
5.5%
글로벌 선도기업 164
 
4.0%
글로벌 강소기업 74
 
1.8%

Length

2024-04-21T11:01:44.895901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:01:45.009215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3072
59.1%
글로벌 1062
 
20.4%
유망기업 596
 
11.5%
초보기업 228
 
4.4%
선도기업 164
 
3.2%
강소기업 74
 
1.4%

수출용주소
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
3072 
서울
308 
경기
 
274
부산
 
69
경북
 
52
Other values (14)
359 

Length

Max length4
Median length4
Mean length3.4869376
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3072
74.3%
서울 308
 
7.5%
경기 274
 
6.6%
부산 69
 
1.7%
경북 52
 
1.3%
인천 49
 
1.2%
경남 47
 
1.1%
대구 40
 
1.0%
충남 37
 
0.9%
충북 34
 
0.8%
Other values (9) 152
 
3.7%

Length

2024-04-21T11:01:45.151586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3072
74.3%
서울 308
 
7.5%
경기 274
 
6.6%
부산 69
 
1.7%
경북 52
 
1.3%
인천 49
 
1.2%
경남 47
 
1.1%
대구 40
 
1.0%
충남 37
 
0.9%
충북 34
 
0.8%
Other values (9) 152
 
3.7%

수출용총점
Real number (ℝ)

MISSING 

Distinct628
Distinct (%)59.1%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean65.108569
Minimum33.75
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:45.277625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.75
5-th percentile43.55
Q156.25
median64.925
Q373.85
95-th percentile86.7975
Maximum100
Range66.25
Interquartile range (IQR)17.6

Descriptive statistics

Standard deviation12.761718
Coefficient of variation (CV)0.19600674
Kurtosis-0.34983553
Mean65.108569
Median Absolute Deviation (MAD)8.8
Skewness0.11561355
Sum69145.3
Variance162.86146
MonotonicityNot monotonic
2024-04-21T11:01:45.418381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72.1 6
 
0.1%
73.3 5
 
0.1%
65.35 5
 
0.1%
79.85 5
 
0.1%
70.25 5
 
0.1%
59.9 5
 
0.1%
68.75 5
 
0.1%
61.45 5
 
0.1%
62.5 5
 
0.1%
61.15 4
 
0.1%
Other values (618) 1012
 
24.5%
(Missing) 3072
74.3%
ValueCountFrequency (%)
33.75 1
< 0.1%
34.7 1
< 0.1%
35.45 1
< 0.1%
35.9 1
< 0.1%
36.15 1
< 0.1%
36.25 1
< 0.1%
37.15 1
< 0.1%
37.2 1
< 0.1%
37.7 1
< 0.1%
38.15 2
< 0.1%
ValueCountFrequency (%)
100.0 2
< 0.1%
99.25 1
< 0.1%
99.0 1
< 0.1%
98.5 1
< 0.1%
98.25 2
< 0.1%
97.75 1
< 0.1%
96.75 1
< 0.1%
96.7 1
< 0.1%
96.55 1
< 0.1%
96.4 1
< 0.1%

수출용수출실적
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)0.6%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean3.7881356
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:45.558825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median2
Q34
95-th percentile10
Maximum10
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.9582917
Coefficient of variation (CV)0.78093606
Kurtosis-0.18342304
Mean3.7881356
Median Absolute Deviation (MAD)0
Skewness1.2563304
Sum4023
Variance8.7514896
MonotonicityNot monotonic
2024-04-21T11:01:45.667392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 734
 
17.8%
10 99
 
2.4%
9 81
 
2.0%
4 66
 
1.6%
6 42
 
1.0%
8 40
 
1.0%
(Missing) 3072
74.3%
ValueCountFrequency (%)
2 734
17.8%
4 66
 
1.6%
6 42
 
1.0%
8 40
 
1.0%
9 81
 
2.0%
10 99
 
2.4%
ValueCountFrequency (%)
10 99
 
2.4%
9 81
 
2.0%
8 40
 
1.0%
6 42
 
1.0%
4 66
 
1.6%
2 734
17.8%

수출용준비점수
Real number (ℝ)

MISSING 

Distinct292
Distinct (%)27.5%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean28.028766
Minimum13.8
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:45.810765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13.8
5-th percentile20.0525
Q125.0625
median28.1
Q331.05
95-th percentile35.845
Maximum39
Range25.2
Interquartile range (IQR)5.9875

Descriptive statistics

Standard deviation4.5571219
Coefficient of variation (CV)0.16258731
Kurtosis-0.25933122
Mean28.028766
Median Absolute Deviation (MAD)3
Skewness-0.059018404
Sum29766.55
Variance20.76736
MonotonicityNot monotonic
2024-04-21T11:01:45.951716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.75 16
 
0.4%
27.05 15
 
0.4%
31.65 14
 
0.3%
28.55 14
 
0.3%
27.95 12
 
0.3%
26.6 12
 
0.3%
28.95 12
 
0.3%
32.4 11
 
0.3%
28.4 11
 
0.3%
31.05 11
 
0.3%
Other values (282) 934
 
22.6%
(Missing) 3072
74.3%
ValueCountFrequency (%)
13.8 1
 
< 0.1%
15.55 1
 
< 0.1%
16.3 1
 
< 0.1%
16.5 1
 
< 0.1%
17.05 2
< 0.1%
17.2 1
 
< 0.1%
17.65 2
< 0.1%
17.8 4
0.1%
17.9 1
 
< 0.1%
17.95 1
 
< 0.1%
ValueCountFrequency (%)
39.0 7
0.2%
38.25 4
0.1%
38.0 2
 
< 0.1%
37.65 3
0.1%
37.5 4
0.1%
37.25 1
 
< 0.1%
37.2 1
 
< 0.1%
37.05 1
 
< 0.1%
36.9 4
0.1%
36.75 5
0.1%

수출용활용점수
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)6.9%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean13.864548
Minimum5.1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:46.090835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.1
5-th percentile8.1
Q111.1
median13.95
Q316.35
95-th percentile19.5
Maximum21
Range15.9
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation3.4632496
Coefficient of variation (CV)0.24979174
Kurtosis-0.73948489
Mean13.864548
Median Absolute Deviation (MAD)2.55
Skewness-0.065459602
Sum14724.15
Variance11.994098
MonotonicityNot monotonic
2024-04-21T11:01:46.230828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.55 41
 
1.0%
16.05 35
 
0.8%
13.05 31
 
0.7%
8.85 30
 
0.7%
10.35 30
 
0.7%
15.9 30
 
0.7%
12.45 29
 
0.7%
13.8 29
 
0.7%
15.3 29
 
0.7%
17.4 28
 
0.7%
Other values (63) 750
 
18.1%
(Missing) 3072
74.3%
ValueCountFrequency (%)
5.1 1
 
< 0.1%
5.85 5
 
0.1%
6.6 11
0.3%
7.2 2
 
< 0.1%
7.35 10
 
0.2%
7.8 1
 
< 0.1%
7.95 9
 
0.2%
8.1 25
0.6%
8.55 3
 
0.1%
8.7 17
0.4%
ValueCountFrequency (%)
21.0 14
0.3%
20.4 3
 
0.1%
20.25 16
0.4%
19.8 1
 
< 0.1%
19.65 17
0.4%
19.5 17
0.4%
19.05 7
 
0.2%
18.9 22
0.5%
18.75 7
 
0.2%
18.3 12
0.3%

수출용심화점수
Real number (ℝ)

MISSING 

Distinct228
Distinct (%)21.5%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean19.427119
Minimum7.3
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:46.390086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.3
5-th percentile11
Q115.95
median19.4
Q322.7
95-th percentile27.75
Maximum30
Range22.7
Interquartile range (IQR)6.75

Descriptive statistics

Standard deviation4.8644243
Coefficient of variation (CV)0.2503935
Kurtosis-0.34381844
Mean19.427119
Median Absolute Deviation (MAD)3.45
Skewness-0.027484685
Sum20631.6
Variance23.662624
MonotonicityNot monotonic
2024-04-21T11:01:46.523557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 25
 
0.6%
14.6 25
 
0.6%
19.4 23
 
0.6%
18.65 21
 
0.5%
20.9 17
 
0.4%
13.85 17
 
0.4%
15.35 17
 
0.4%
16.55 16
 
0.4%
16.7 16
 
0.4%
21.75 15
 
0.4%
Other values (218) 870
 
21.0%
(Missing) 3072
74.3%
ValueCountFrequency (%)
7.3 3
0.1%
8.05 3
0.1%
8.3 5
0.1%
8.65 1
 
< 0.1%
8.9 4
0.1%
9.05 7
0.2%
9.25 1
 
< 0.1%
9.3 1
 
< 0.1%
9.4 2
 
< 0.1%
9.65 5
0.1%
ValueCountFrequency (%)
30.0 25
0.6%
29.4 4
 
0.1%
29.25 5
 
0.1%
29.0 1
 
< 0.1%
28.8 3
 
0.1%
28.65 3
 
0.1%
28.5 3
 
0.1%
28.25 1
 
< 0.1%
28.2 4
 
0.1%
28.05 1
 
< 0.1%

수출용비전마인드
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)0.8%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean0.8429661
Minimum0.33
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:46.638787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.33
5-th percentile0.58
Q10.75
median0.83
Q31
95-th percentile1
Maximum1
Range0.67
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.13951565
Coefficient of variation (CV)0.16550564
Kurtosis-0.25722634
Mean0.8429661
Median Absolute Deviation (MAD)0.09
Skewness-0.62727378
Sum895.23
Variance0.019464615
MonotonicityNot monotonic
2024-04-21T11:01:46.752275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1.0 306
 
7.4%
0.83 230
 
5.6%
0.92 170
 
4.1%
0.75 169
 
4.1%
0.67 105
 
2.5%
0.58 57
 
1.4%
0.5 17
 
0.4%
0.42 7
 
0.2%
0.33 1
 
< 0.1%
(Missing) 3072
74.3%
ValueCountFrequency (%)
0.33 1
 
< 0.1%
0.42 7
 
0.2%
0.5 17
 
0.4%
0.58 57
 
1.4%
0.67 105
 
2.5%
0.75 169
4.1%
0.83 230
5.6%
0.92 170
4.1%
1.0 306
7.4%
ValueCountFrequency (%)
1.0 306
7.4%
0.92 170
4.1%
0.83 230
5.6%
0.75 169
4.1%
0.67 105
 
2.5%
0.58 57
 
1.4%
0.5 17
 
0.4%
0.42 7
 
0.2%
0.33 1
 
< 0.1%

수출용인프라
Real number (ℝ)

MISSING 

Distinct46
Distinct (%)4.3%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean0.74050847
Minimum0.34
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:46.883047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.34
5-th percentile0.52
Q10.65
median0.76
Q30.82
95-th percentile0.95
Maximum1
Range0.66
Interquartile range (IQR)0.17

Descriptive statistics

Standard deviation0.12906218
Coefficient of variation (CV)0.17428859
Kurtosis-0.21938192
Mean0.74050847
Median Absolute Deviation (MAD)0.09
Skewness-0.24412643
Sum786.42
Variance0.016657046
MonotonicityNot monotonic
2024-04-21T11:01:47.013295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0.76 105
 
2.5%
0.82 100
 
2.4%
0.87 75
 
1.8%
0.71 71
 
1.7%
0.55 49
 
1.2%
0.81 48
 
1.2%
0.61 42
 
1.0%
0.7 42
 
1.0%
0.77 41
 
1.0%
0.65 39
 
0.9%
Other values (36) 450
 
10.9%
(Missing) 3072
74.3%
ValueCountFrequency (%)
0.34 2
 
< 0.1%
0.38 3
 
0.1%
0.4 2
 
< 0.1%
0.42 9
 
0.2%
0.44 1
 
< 0.1%
0.47 7
 
0.2%
0.49 23
0.6%
0.5 1
 
< 0.1%
0.52 10
0.2%
0.53 4
 
0.1%
ValueCountFrequency (%)
1.0 32
 
0.8%
0.95 34
 
0.8%
0.94 28
 
0.7%
0.92 1
 
< 0.1%
0.9 3
 
0.1%
0.89 36
 
0.9%
0.87 75
1.8%
0.85 7
 
0.2%
0.84 19
 
0.5%
0.82 100
2.4%

수출용인력및자금
Real number (ℝ)

MISSING 

Distinct64
Distinct (%)6.0%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean0.64038606
Minimum0.25
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:47.141421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.25
5-th percentile0.41
Q10.54
median0.63
Q30.73
95-th percentile0.9
Maximum1
Range0.75
Interquartile range (IQR)0.19

Descriptive statistics

Standard deviation0.14774887
Coefficient of variation (CV)0.23071843
Kurtosis-0.22308411
Mean0.64038606
Median Absolute Deviation (MAD)0.09
Skewness0.25727871
Sum680.09
Variance0.021829728
MonotonicityNot monotonic
2024-04-21T11:01:47.283652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.67 57
 
1.4%
0.54 53
 
1.3%
0.72 42
 
1.0%
0.63 41
 
1.0%
0.59 37
 
0.9%
0.64 36
 
0.9%
0.62 34
 
0.8%
0.6 32
 
0.8%
0.71 31
 
0.7%
0.74 30
 
0.7%
Other values (54) 669
 
16.2%
(Missing) 3072
74.3%
ValueCountFrequency (%)
0.25 1
 
< 0.1%
0.29 4
 
0.1%
0.32 2
 
< 0.1%
0.33 7
 
0.2%
0.34 1
 
< 0.1%
0.36 4
 
0.1%
0.37 13
0.3%
0.39 3
 
0.1%
0.4 4
 
0.1%
0.41 26
0.6%
ValueCountFrequency (%)
1.0 23
0.6%
0.96 14
0.3%
0.94 3
 
0.1%
0.93 2
 
< 0.1%
0.92 11
0.3%
0.9 5
 
0.1%
0.89 7
 
0.2%
0.88 4
 
0.1%
0.87 20
0.5%
0.86 9
 
0.2%

수출용의사소통
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)0.9%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean0.76511299
Minimum0.25
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:47.398418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.25
5-th percentile0.42
Q10.67
median0.75
Q30.92
95-th percentile1
Maximum1
Range0.75
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.17720507
Coefficient of variation (CV)0.2316064
Kurtosis-0.60119953
Mean0.76511299
Median Absolute Deviation (MAD)0.17
Skewness-0.4243935
Sum812.55
Variance0.031401637
MonotonicityNot monotonic
2024-04-21T11:01:47.509515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.75 187
 
4.5%
1.0 182
 
4.4%
0.92 169
 
4.1%
0.67 155
 
3.7%
0.83 137
 
3.3%
0.58 102
 
2.5%
0.5 67
 
1.6%
0.42 45
 
1.1%
0.33 15
 
0.4%
0.25 3
 
0.1%
(Missing) 3072
74.3%
ValueCountFrequency (%)
0.25 3
 
0.1%
0.33 15
 
0.4%
0.42 45
 
1.1%
0.5 67
 
1.6%
0.58 102
2.5%
0.67 155
3.7%
0.75 187
4.5%
0.83 137
3.3%
0.92 169
4.1%
1.0 182
4.4%
ValueCountFrequency (%)
1.0 182
4.4%
0.92 169
4.1%
0.83 137
3.3%
0.75 187
4.5%
0.67 155
3.7%
0.58 102
2.5%
0.5 67
 
1.6%
0.42 45
 
1.1%
0.33 15
 
0.4%
0.25 3
 
0.1%

수출용판촉온라인
Real number (ℝ)

MISSING 

Distinct44
Distinct (%)4.1%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean0.58284369
Minimum0.24
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:47.642868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.24
5-th percentile0.3
Q10.43
median0.59
Q30.71
95-th percentile0.89
Maximum1
Range0.76
Interquartile range (IQR)0.28

Descriptive statistics

Standard deviation0.1848565
Coefficient of variation (CV)0.31716308
Kurtosis-0.76076959
Mean0.58284369
Median Absolute Deviation (MAD)0.13
Skewness0.17585348
Sum618.98
Variance0.034171925
MonotonicityNot monotonic
2024-04-21T11:01:47.765711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.36 66
 
1.6%
0.3 64
 
1.5%
0.65 62
 
1.5%
0.59 57
 
1.4%
0.54 53
 
1.3%
0.41 52
 
1.3%
0.71 50
 
1.2%
0.76 50
 
1.2%
0.48 47
 
1.1%
0.53 45
 
1.1%
Other values (34) 516
 
12.5%
(Missing) 3072
74.3%
ValueCountFrequency (%)
0.24 20
 
0.5%
0.29 6
 
0.1%
0.3 64
1.5%
0.34 3
 
0.1%
0.35 34
0.8%
0.36 66
1.6%
0.4 10
 
0.2%
0.41 52
1.3%
0.43 32
0.8%
0.45 1
 
< 0.1%
ValueCountFrequency (%)
1.0 15
 
0.4%
0.95 6
 
0.1%
0.94 26
0.6%
0.9 1
 
< 0.1%
0.89 26
0.6%
0.88 12
 
0.3%
0.84 15
 
0.4%
0.83 42
1.0%
0.81 7
 
0.2%
0.79 1
 
< 0.1%

수출용네트워크
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)0.9%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean0.66390772
Minimum0.25
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:47.872948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.25
5-th percentile0.25
Q10.5
median0.67
Q30.75
95-th percentile1
Maximum1
Range0.75
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.19216874
Coefficient of variation (CV)0.28945098
Kurtosis-0.41914345
Mean0.66390772
Median Absolute Deviation (MAD)0.16
Skewness-0.21993726
Sum705.07
Variance0.036928825
MonotonicityNot monotonic
2024-04-21T11:01:48.219617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.75 238
 
5.8%
0.67 148
 
3.6%
0.5 146
 
3.5%
0.58 138
 
3.3%
0.83 105
 
2.5%
1.0 87
 
2.1%
0.42 62
 
1.5%
0.92 56
 
1.4%
0.25 55
 
1.3%
0.33 27
 
0.7%
(Missing) 3072
74.3%
ValueCountFrequency (%)
0.25 55
 
1.3%
0.33 27
 
0.7%
0.42 62
 
1.5%
0.5 146
3.5%
0.58 138
3.3%
0.67 148
3.6%
0.75 238
5.8%
0.83 105
2.5%
0.92 56
 
1.4%
1.0 87
 
2.1%
ValueCountFrequency (%)
1.0 87
 
2.1%
0.92 56
 
1.4%
0.83 105
2.5%
0.75 238
5.8%
0.67 148
3.6%
0.58 138
3.3%
0.5 146
3.5%
0.42 62
 
1.5%
0.33 27
 
0.7%
0.25 55
 
1.3%

수출용시장전략
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)4.4%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean0.59278719
Minimum0.23
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:48.335333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.23
5-th percentile0.29
Q10.45
median0.56
Q30.73
95-th percentile0.94
Maximum1
Range0.77
Interquartile range (IQR)0.28

Descriptive statistics

Standard deviation0.17902698
Coefficient of variation (CV)0.30200885
Kurtosis-0.37966953
Mean0.59278719
Median Absolute Deviation (MAD)0.12
Skewness0.22375796
Sum629.54
Variance0.03205066
MonotonicityNot monotonic
2024-04-21T11:01:48.471169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.45 142
 
3.4%
0.68 79
 
1.9%
0.61 72
 
1.7%
0.55 68
 
1.6%
0.78 67
 
1.6%
0.73 63
 
1.5%
0.5 52
 
1.3%
0.39 41
 
1.0%
0.56 40
 
1.0%
0.51 40
 
1.0%
Other values (37) 398
 
9.6%
(Missing) 3072
74.3%
ValueCountFrequency (%)
0.23 30
0.7%
0.28 20
0.5%
0.29 8
 
0.2%
0.33 17
0.4%
0.34 18
0.4%
0.35 1
 
< 0.1%
0.38 6
 
0.1%
0.39 41
1.0%
0.4 9
 
0.2%
0.43 5
 
0.1%
ValueCountFrequency (%)
1.0 35
0.8%
0.95 15
0.4%
0.94 6
 
0.1%
0.9 11
 
0.3%
0.89 7
 
0.2%
0.88 1
 
< 0.1%
0.85 1
 
< 0.1%
0.84 21
0.5%
0.83 17
0.4%
0.8 2
 
< 0.1%

수출용제품
Real number (ℝ)

MISSING 

Distinct43
Distinct (%)4.0%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean0.70623352
Minimum0.26
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:48.597624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.26
5-th percentile0.44
Q10.59
median0.7
Q30.85
95-th percentile1
Maximum1
Range0.74
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.16556229
Coefficient of variation (CV)0.23442995
Kurtosis-0.5764499
Mean0.70623352
Median Absolute Deviation (MAD)0.13
Skewness-0.21246215
Sum750.02
Variance0.027410871
MonotonicityNot monotonic
2024-04-21T11:01:48.750762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.67 120
 
2.9%
0.85 93
 
2.2%
0.52 89
 
2.2%
0.59 71
 
1.7%
0.74 62
 
1.5%
0.92 59
 
1.4%
1.0 56
 
1.4%
0.78 49
 
1.2%
0.93 43
 
1.0%
0.77 39
 
0.9%
Other values (33) 381
 
9.2%
(Missing) 3072
74.3%
ValueCountFrequency (%)
0.26 8
 
0.2%
0.33 5
 
0.1%
0.34 3
 
0.1%
0.37 20
0.5%
0.39 1
 
< 0.1%
0.41 8
 
0.2%
0.43 1
 
< 0.1%
0.44 37
0.9%
0.46 9
 
0.2%
0.48 5
 
0.1%
ValueCountFrequency (%)
1.0 56
1.4%
0.93 43
1.0%
0.92 59
1.4%
0.89 7
 
0.2%
0.87 17
 
0.4%
0.85 93
2.2%
0.83 25
 
0.6%
0.82 21
 
0.5%
0.81 11
 
0.3%
0.8 5
 
0.1%

수출용매출금액
Real number (ℝ)

MISSING  SKEWED 

Distinct735
Distinct (%)69.2%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean4.0357891 × 1011
Minimum0
Maximum3.33 × 1014
Zeros8
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:48.920898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10724257
Q12 × 108
median8.9683319 × 108
Q35.976036 × 109
95-th percentile1.5 × 1011
Maximum3.33 × 1014
Range3.33 × 1014
Interquartile range (IQR)5.776036 × 109

Descriptive statistics

Standard deviation1.0248533 × 1013
Coefficient of variation (CV)25.394123
Kurtosis1048.3916
Mean4.0357891 × 1011
Median Absolute Deviation (MAD)8.4979043 × 108
Skewness32.282465
Sum4.2860081 × 1014
Variance1.0503242 × 1026
MonotonicityNot monotonic
2024-04-21T11:01:49.053164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000000 23
 
0.6%
200000000 19
 
0.5%
600000000 17
 
0.4%
500000000 16
 
0.4%
1000000000 14
 
0.3%
300000000 12
 
0.3%
400000000 12
 
0.3%
50000000 9
 
0.2%
2000000000 9
 
0.2%
150000000 8
 
0.2%
Other values (725) 923
 
22.3%
(Missing) 3072
74.3%
ValueCountFrequency (%)
0 8
0.2%
1 1
 
< 0.1%
6 1
 
< 0.1%
56 1
 
< 0.1%
84 1
 
< 0.1%
500 1
 
< 0.1%
1000 3
 
0.1%
1330 1
 
< 0.1%
1770 1
 
< 0.1%
2200 1
 
< 0.1%
ValueCountFrequency (%)
333000000000000 1
< 0.1%
16000000000000 1
< 0.1%
14000000000000 1
< 0.1%
11300000000000 1
< 0.1%
6780000000000 1
< 0.1%
6570000000000 1
< 0.1%
3850000000000 1
< 0.1%
3100000000000 1
< 0.1%
2780000000000 1
< 0.1%
1790000000000 1
< 0.1%

수출용수출금액
Real number (ℝ)

MISSING  SKEWED 

Distinct810
Distinct (%)76.3%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean4.96721 × 108
Minimum1
Maximum4 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:49.217412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1000
Q17918.75
median43243
Q3458534
95-th percentile37187797
Maximum4 × 1011
Range4 × 1011
Interquartile range (IQR)450615.25

Descriptive statistics

Standard deviation1.2540672 × 1010
Coefficient of variation (CV)25.246914
Kurtosis974.96722
Mean4.96721 × 108
Median Absolute Deviation (MAD)41063
Skewness30.797762
Sum5.2751771 × 1011
Variance1.5726847 × 1020
MonotonicityNot monotonic
2024-04-21T11:01:49.371351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000 29
 
0.7%
10000 26
 
0.6%
20000 20
 
0.5%
100000 13
 
0.3%
50000 12
 
0.3%
2000 11
 
0.3%
3000 10
 
0.2%
5000 9
 
0.2%
70000 8
 
0.2%
60000 8
 
0.2%
Other values (800) 916
 
22.2%
(Missing) 3072
74.3%
ValueCountFrequency (%)
1 1
< 0.1%
10 1
< 0.1%
20 1
< 0.1%
30 2
< 0.1%
60 1
< 0.1%
77 1
< 0.1%
100 2
< 0.1%
116 1
< 0.1%
121 1
< 0.1%
135 1
< 0.1%
ValueCountFrequency (%)
400000000000 1
< 0.1%
83000000000 1
< 0.1%
10000000000 1
< 0.1%
7500000000 1
< 0.1%
5475000000 1
< 0.1%
5000000000 1
< 0.1%
4000000000 1
< 0.1%
1500000000 1
< 0.1%
1377923308 1
< 0.1%
1000000000 1
< 0.1%

수출용수출제품코드
Real number (ℝ)

MISSING 

Distinct243
Distinct (%)22.9%
Missing3072
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean4792.4228
Minimum116
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-21T11:01:49.510523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum116
5-th percentile162
Q12275
median5129
Q37412
95-th percentile9900
Maximum9999
Range9883
Interquartile range (IQR)5137

Descriptive statistics

Standard deviation3032.7153
Coefficient of variation (CV)0.63281463
Kurtosis-1.2614461
Mean4792.4228
Median Absolute Deviation (MAD)2854
Skewness0.039639269
Sum5089553
Variance9197361.9
MonotonicityNot monotonic
2024-04-21T11:01:49.644133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2275 178
 
4.3%
7331 52
 
1.3%
5900 44
 
1.1%
169 41
 
1.0%
9900 32
 
0.8%
3109 24
 
0.6%
7420 23
 
0.6%
9999 19
 
0.5%
7901 16
 
0.4%
4490 13
 
0.3%
Other values (233) 620
 
15.0%
(Missing) 3072
74.3%
ValueCountFrequency (%)
116 1
 
< 0.1%
121 1
 
< 0.1%
131 1
 
< 0.1%
134 3
0.1%
136 2
< 0.1%
143 4
0.1%
149 1
 
< 0.1%
151 2
< 0.1%
152 1
 
< 0.1%
153 4
0.1%
ValueCountFrequency (%)
9999 19
0.5%
9996 1
 
< 0.1%
9993 2
 
< 0.1%
9992 1
 
< 0.1%
9926 3
 
0.1%
9900 32
0.8%
9800 1
 
< 0.1%
9791 3
 
0.1%
9741 1
 
< 0.1%
9721 3
 
0.1%

수출용수출제품명
Text

MISSING 

Distinct226
Distinct (%)22.1%
Missing3112
Missing (%)75.3%
Memory size32.4 KiB
2024-04-21T11:01:49.900352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length4.9041096
Min length1

Characters and Unicode

Total characters5012
Distinct characters252
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)9.6%

Sample

1st row아세테이트섬유
2nd row철강재체인
3rd row기타화학공업제품
4th row의료용기기부품
5th row커피류
ValueCountFrequency (%)
화장품 178
 
16.9%
의료용기기 52
 
4.9%
기타생활용품 44
 
4.2%
기타농산가공품 41
 
3.9%
기타잡제품 32
 
3.0%
기타플라스틱제품 24
 
2.3%
자동차부품 23
 
2.2%
기타서비스 19
 
1.8%
기타기계류 16
 
1.5%
음료 13
 
1.2%
Other values (227) 612
58.1%
2024-04-21T11:01:50.275612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 674
 
13.4%
품 498
 
9.9%
타 405
 
8.1%
화 208
 
4.2%
장 204
 
4.1%
용 177
 
3.5%
제 162
 
3.2%
의 105
 
2.1%
료 95
 
1.9%
류 91
 
1.8%
Other values (242) 2393
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4900
97.8%
Lowercase Letter 68
 
1.4%
Space Separator 32
 
0.6%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 674
 
13.8%
품 498
 
10.2%
타 405
 
8.3%
화 208
 
4.2%
장 204
 
4.2%
용 177
 
3.6%
제 162
 
3.3%
의 105
 
2.1%
료 95
 
1.9%
류 91
 
1.9%
Other values (226) 2281
46.6%
Lowercase Letter
ValueCountFrequency (%)
e 12
17.6%
r 11
16.2%
c 10
14.7%
t 8
11.8%
y 5
7.4%
i 5
7.4%
l 5
7.4%
a 5
7.4%
o 3
 
4.4%
h 2
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
V 1
50.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4900
97.8%
Latin 70
 
1.4%
Common 42
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 674
 
13.8%
품 498
 
10.2%
타 405
 
8.3%
화 208
 
4.2%
장 204
 
4.2%
용 177
 
3.6%
제 162
 
3.3%
의 105
 
2.1%
료 95
 
1.9%
류 91
 
1.9%
Other values (226) 2281
46.6%
Latin
ValueCountFrequency (%)
e 12
17.1%
r 11
15.7%
c 10
14.3%
t 8
11.4%
y 5
7.1%
i 5
7.1%
l 5
7.1%
a 5
7.1%
o 3
 
4.3%
h 2
 
2.9%
Other values (3) 4
 
5.7%
Common
ValueCountFrequency (%)
32
76.2%
) 5
 
11.9%
( 5
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4900
97.8%
ASCII 112
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 674
 
13.8%
품 498
 
10.2%
타 405
 
8.3%
화 208
 
4.2%
장 204
 
4.2%
용 177
 
3.6%
제 162
 
3.3%
의 105
 
2.1%
료 95
 
1.9%
류 91
 
1.9%
Other values (226) 2281
46.6%
ASCII
ValueCountFrequency (%)
32
28.6%
e 12
 
10.7%
r 11
 
9.8%
c 10
 
8.9%
t 8
 
7.1%
y 5
 
4.5%
) 5
 
4.5%
i 5
 
4.5%
l 5
 
4.5%
a 5
 
4.5%
Other values (6) 14
12.5%

수출용주요수출국가1
Text

MISSING 

Distinct156
Distinct (%)17.7%
Missing3252
Missing (%)78.7%
Memory size32.4 KiB
2024-04-21T11:01:50.565859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length2
Mean length2.9104308
Min length1

Characters and Unicode

Total characters2567
Distinct characters248
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)11.7%

Sample

1st row스페인
2nd rowRoller Chain
3rd row베트남
4th row유럽
5th row유럽
ValueCountFrequency (%)
미국 222
24.0%
중국 110
 
11.9%
일본 86
 
9.3%
베트남 63
 
6.8%
유럽 36
 
3.9%
북미 22
 
2.4%
러시아 21
 
2.3%
동남아 19
 
2.1%
동남아시아 14
 
1.5%
태국 13
 
1.4%
Other values (164) 319
34.5%
2024-04-21T11:01:51.041551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 354
 
13.8%
미 269
 
10.5%
아 136
 
5.3%
중 130
 
5.1%
남 106
 
4.1%
일 93
 
3.6%
본 86
 
3.4%
시 71
 
2.8%
트 69
 
2.7%
베 68
 
2.6%
Other values (238) 1185
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2322
90.5%
Lowercase Letter 98
 
3.8%
Uppercase Letter 71
 
2.8%
Space Separator 52
 
2.0%
Other Punctuation 9
 
0.4%
Close Punctuation 7
 
0.3%
Open Punctuation 7
 
0.3%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 354
 
15.2%
미 269
 
11.6%
아 136
 
5.9%
중 130
 
5.6%
남 106
 
4.6%
일 93
 
4.0%
본 86
 
3.7%
시 71
 
3.1%
트 69
 
3.0%
베 68
 
2.9%
Other values (193) 940
40.5%
Lowercase Letter
ValueCountFrequency (%)
e 11
11.2%
r 11
11.2%
o 10
10.2%
a 9
9.2%
s 8
8.2%
i 7
 
7.1%
t 7
 
7.1%
l 6
 
6.1%
c 6
 
6.1%
m 5
 
5.1%
Other values (9) 18
18.4%
Uppercase Letter
ValueCountFrequency (%)
U 10
14.1%
A 9
12.7%
E 8
11.3%
S 6
 
8.5%
C 5
 
7.0%
O 5
 
7.0%
N 4
 
5.6%
G 3
 
4.2%
L 3
 
4.2%
T 3
 
4.2%
Other values (9) 15
21.1%
Other Punctuation
ValueCountFrequency (%)
, 5
55.6%
/ 3
33.3%
. 1
 
11.1%
Space Separator
ValueCountFrequency (%)
52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2322
90.5%
Latin 169
 
6.6%
Common 76
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 354
 
15.2%
미 269
 
11.6%
아 136
 
5.9%
중 130
 
5.6%
남 106
 
4.6%
일 93
 
4.0%
본 86
 
3.7%
시 71
 
3.1%
트 69
 
3.0%
베 68
 
2.9%
Other values (193) 940
40.5%
Latin
ValueCountFrequency (%)
e 11
 
6.5%
r 11
 
6.5%
U 10
 
5.9%
o 10
 
5.9%
A 9
 
5.3%
a 9
 
5.3%
E 8
 
4.7%
s 8
 
4.7%
i 7
 
4.1%
t 7
 
4.1%
Other values (28) 79
46.7%
Common
ValueCountFrequency (%)
52
68.4%
) 7
 
9.2%
( 7
 
9.2%
, 5
 
6.6%
/ 3
 
3.9%
` 1
 
1.3%
. 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2322
90.5%
ASCII 245
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 354
 
15.2%
미 269
 
11.6%
아 136
 
5.9%
중 130
 
5.6%
남 106
 
4.6%
일 93
 
4.0%
본 86
 
3.7%
시 71
 
3.1%
트 69
 
3.0%
베 68
 
2.9%
Other values (193) 940
40.5%
ASCII
ValueCountFrequency (%)
52
21.2%
e 11
 
4.5%
r 11
 
4.5%
U 10
 
4.1%
o 10
 
4.1%
A 9
 
3.7%
a 9
 
3.7%
E 8
 
3.3%
s 8
 
3.3%
) 7
 
2.9%
Other values (35) 110
44.9%

수출용주요수출국가2
Text

MISSING 

Distinct157
Distinct (%)18.6%
Missing3291
Missing (%)79.6%
Memory size32.4 KiB
2024-04-21T11:01:51.331998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length2
Mean length3.0142349
Min length2

Characters and Unicode

Total characters2541
Distinct characters250
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)12.3%

Sample

1st row터키
2nd rowleaf Chain
3rd row인도네시아
4th row미국
5th row대만
ValueCountFrequency (%)
중국 93
 
10.6%
일본 83
 
9.5%
미국 79
 
9.0%
유럽 79
 
9.0%
베트남 40
 
4.6%
동남아 32
 
3.6%
캐나다 27
 
3.1%
인도네시아 25
 
2.9%
러시아 22
 
2.5%
대만 21
 
2.4%
Other values (159) 376
42.9%
2024-04-21T11:01:51.775663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 211
 
8.3%
아 170
 
6.7%
중 119
 
4.7%
미 107
 
4.2%
일 101
 
4.0%
남 97
 
3.8%
시 89
 
3.5%
유 88
 
3.5%
럽 84
 
3.3%
본 83
 
3.3%
Other values (240) 1392
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2317
91.2%
Lowercase Letter 82
 
3.2%
Uppercase Letter 61
 
2.4%
Space Separator 48
 
1.9%
Other Punctuation 13
 
0.5%
Close Punctuation 10
 
0.4%
Open Punctuation 10
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 211
 
9.1%
아 170
 
7.3%
중 119
 
5.1%
미 107
 
4.6%
일 101
 
4.4%
남 97
 
4.2%
시 89
 
3.8%
유 88
 
3.8%
럽 84
 
3.6%
본 83
 
3.6%
Other values (198) 1168
50.4%
Uppercase Letter
ValueCountFrequency (%)
E 10
16.4%
A 8
13.1%
C 7
11.5%
U 6
9.8%
I 5
8.2%
S 5
8.2%
P 4
 
6.6%
N 3
 
4.9%
L 3
 
4.9%
D 2
 
3.3%
Other values (8) 8
13.1%
Lowercase Letter
ValueCountFrequency (%)
e 11
13.4%
a 10
12.2%
i 10
12.2%
s 7
8.5%
p 7
8.5%
r 5
 
6.1%
n 5
 
6.1%
l 4
 
4.9%
c 4
 
4.9%
o 4
 
4.9%
Other values (7) 15
18.3%
Other Punctuation
ValueCountFrequency (%)
, 8
61.5%
. 3
 
23.1%
; 1
 
7.7%
& 1
 
7.7%
Space Separator
ValueCountFrequency (%)
48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2317
91.2%
Latin 143
 
5.6%
Common 81
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 211
 
9.1%
아 170
 
7.3%
중 119
 
5.1%
미 107
 
4.6%
일 101
 
4.4%
남 97
 
4.2%
시 89
 
3.8%
유 88
 
3.8%
럽 84
 
3.6%
본 83
 
3.6%
Other values (198) 1168
50.4%
Latin
ValueCountFrequency (%)
e 11
 
7.7%
a 10
 
7.0%
E 10
 
7.0%
i 10
 
7.0%
A 8
 
5.6%
s 7
 
4.9%
C 7
 
4.9%
p 7
 
4.9%
U 6
 
4.2%
r 5
 
3.5%
Other values (25) 62
43.4%
Common
ValueCountFrequency (%)
48
59.3%
) 10
 
12.3%
( 10
 
12.3%
, 8
 
9.9%
. 3
 
3.7%
; 1
 
1.2%
& 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2317
91.2%
ASCII 224
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 211
 
9.1%
아 170
 
7.3%
중 119
 
5.1%
미 107
 
4.6%
일 101
 
4.4%
남 97
 
4.2%
시 89
 
3.8%
유 88
 
3.8%
럽 84
 
3.6%
본 83
 
3.6%
Other values (198) 1168
50.4%
ASCII
ValueCountFrequency (%)
48
21.4%
e 11
 
4.9%
) 10
 
4.5%
( 10
 
4.5%
a 10
 
4.5%
E 10
 
4.5%
i 10
 
4.5%
, 8
 
3.6%
A 8
 
3.6%
s 7
 
3.1%
Other values (32) 92
41.1%

수출용주요수출국가3
Text

MISSING 

Distinct156
Distinct (%)20.0%
Missing3353
Missing (%)81.1%
Memory size32.4 KiB
2024-04-21T11:01:51.960359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length2
Mean length2.9743918
Min length2

Characters and Unicode

Total characters2323
Distinct characters239
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)14.1%

Sample

1st row미국
2nd rowConveyor Chain
3rd row말레이시아
4th row일본
5th row태국
ValueCountFrequency (%)
일본 83
 
10.2%
미국 66
 
8.1%
유럽 66
 
8.1%
중국 54
 
6.7%
베트남 41
 
5.0%
러시아 29
 
3.6%
중동 25
 
3.1%
동남아 24
 
3.0%
호주 22
 
2.7%
인도네시아 19
 
2.3%
Other values (152) 383
47.2%
2024-04-21T11:01:52.301479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 191
 
8.2%
국 147
 
6.3%
미 113
 
4.9%
시 101
 
4.3%
남 98
 
4.2%
일 95
 
4.1%
중 90
 
3.9%
본 84
 
3.6%
유 71
 
3.1%
럽 70
 
3.0%
Other values (229) 1263
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2135
91.9%
Lowercase Letter 64
 
2.8%
Uppercase Letter 61
 
2.6%
Space Separator 43
 
1.9%
Other Punctuation 11
 
0.5%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 191
 
8.9%
국 147
 
6.9%
미 113
 
5.3%
시 101
 
4.7%
남 98
 
4.6%
일 95
 
4.4%
중 90
 
4.2%
본 84
 
3.9%
유 71
 
3.3%
럽 70
 
3.3%
Other values (183) 1075
50.4%
Lowercase Letter
ValueCountFrequency (%)
e 10
15.6%
n 8
12.5%
a 6
9.4%
r 6
9.4%
o 6
9.4%
i 5
7.8%
t 3
 
4.7%
v 3
 
4.7%
y 3
 
4.7%
h 2
 
3.1%
Other values (10) 12
18.8%
Uppercase Letter
ValueCountFrequency (%)
I 11
18.0%
C 10
16.4%
S 8
13.1%
U 6
9.8%
A 5
8.2%
P 4
 
6.6%
E 4
 
6.6%
B 3
 
4.9%
N 2
 
3.3%
J 1
 
1.6%
Other values (7) 7
11.5%
Other Punctuation
ValueCountFrequency (%)
, 6
54.5%
/ 2
 
18.2%
; 1
 
9.1%
& 1
 
9.1%
* 1
 
9.1%
Space Separator
ValueCountFrequency (%)
43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2135
91.9%
Latin 125
 
5.4%
Common 63
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 191
 
8.9%
국 147
 
6.9%
미 113
 
5.3%
시 101
 
4.7%
남 98
 
4.6%
일 95
 
4.4%
중 90
 
4.2%
본 84
 
3.9%
유 71
 
3.3%
럽 70
 
3.3%
Other values (183) 1075
50.4%
Latin
ValueCountFrequency (%)
I 11
 
8.8%
C 10
 
8.0%
e 10
 
8.0%
n 8
 
6.4%
S 8
 
6.4%
a 6
 
4.8%
U 6
 
4.8%
r 6
 
4.8%
o 6
 
4.8%
i 5
 
4.0%
Other values (27) 49
39.2%
Common
ValueCountFrequency (%)
43
68.3%
, 6
 
9.5%
) 4
 
6.3%
( 4
 
6.3%
/ 2
 
3.2%
; 1
 
1.6%
& 1
 
1.6%
- 1
 
1.6%
* 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2135
91.9%
ASCII 188
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 191
 
8.9%
국 147
 
6.9%
미 113
 
5.3%
시 101
 
4.7%
남 98
 
4.6%
일 95
 
4.4%
중 90
 
4.2%
본 84
 
3.9%
유 71
 
3.3%
럽 70
 
3.3%
Other values (183) 1075
50.4%
ASCII
ValueCountFrequency (%)
43
22.9%
I 11
 
5.9%
C 10
 
5.3%
e 10
 
5.3%
n 8
 
4.3%
S 8
 
4.3%
a 6
 
3.2%
U 6
 
3.2%
r 6
 
3.2%
o 6
 
3.2%
Other values (36) 74
39.4%

Sample

번호내수용기업유형1내수용기업유형2내수용역량등급내수용주소내수용총점내수용수출의지내수용기초자원내수용수출인프라내수용마케팅네트워크내수용수출제품코드내수용수출제품명내수용주요수출국가1내수용주요수출국가2내수용주요수출국가3수출용기업유형1수출용기업유형2수출용역량등급수출용주소수출용총점수출용수출실적수출용준비점수수출용활용점수수출용심화점수수출용비전마인드수출용인프라수출용인력및자금수출용의사소통수출용판촉온라인수출용네트워크수출용시장전략수출용제품수출용매출금액수출용수출금액수출용수출제품코드수출용수출제품명수출용주요수출국가1수출용주요수출국가2수출용주요수출국가3
01중소기업제조기업성장내수기업경기60.8315.014.511.8319.58151계측기베트남인도인도네시아<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12중견기업제조기업성장내수기업서울72.0824.7514.514.3318.59926<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23중소기업제조기업성장내수기업경기61.9223.2514.512.6711.55429기타취미오락용구유럽동남아시아북아메리카<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34중소기업제조기업성장내수기업경남70.019.516.012.522.08269기타조명기기<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45중소기업제조기업,서비스기업성장내수기업서울65.7522.2515.010.518.08289<NA>아르헨티나뉴질랜드유럽<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56중소기업제조기업초보내수기업경기51.1720.012.09.679.57331의료용기기<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
67중소기업제조기업초보내수기업인천50.9219.2511.09.1711.57242식품포장기계<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
78중소기업제조기업초보내수기업대전38.1713.58.55.6710.59413안경렌즈미국<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
89중소기업제조기업성장내수기업서울67.3322.510.510.8323.59999기타서비스ㅁ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
910중소기업수출중개기업(오퍼상,에이전트 등)초보내수기업서울52.5816.2512.512.3311.57331의료용기기미국EU중동<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
번호내수용기업유형1내수용기업유형2내수용역량등급내수용주소내수용총점내수용수출의지내수용기초자원내수용수출인프라내수용마케팅네트워크내수용수출제품코드내수용수출제품명내수용주요수출국가1내수용주요수출국가2내수용주요수출국가3수출용기업유형1수출용기업유형2수출용역량등급수출용주소수출용총점수출용수출실적수출용준비점수수출용활용점수수출용심화점수수출용비전마인드수출용인프라수출용인력및자금수출용의사소통수출용판촉온라인수출용네트워크수출용시장전략수출용제품수출용매출금액수출용수출금액수출용수출제품코드수출용수출제품명수출용주요수출국가1수출용주요수출국가2수출용주요수출국가3
41244125<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중소기업제조기업글로벌 강소기업대전85.4835.418.323.71.00.890.871.00.780.750.780.85123366317191027800155인삼류<NA><NA><NA>
41254126<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중소기업수출중개기업(오퍼상,에이전트 등)글로벌 유망기업부산58.45228.9511.116.40.920.710.670.670.430.50.550.59430000000600002262의약품<NA><NA><NA>
41264127<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중소기업제조기업글로벌 초보기업경기51.6227.058.114.450.750.820.580.420.360.420.450.594150000000850005414골프용품독일영국스웨덴
41274128<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중소기업제조기업글로벌 유망기업서울58.45226.4510.219.80.830.650.620.580.410.580.610.89134507700200005163<NA>중국대만미국
41284129<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중소기업제조기업글로벌 유망기업전남65.1226.9515.620.551.00.820.450.920.610.750.560.78150000000100002275화장품러시아동남아유럽
41294130<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중소기업제조기업글로벌 유망기업경남62.5227.0513.819.651.00.670.550.750.590.670.560.77838513019313133103필름류베트남홍콩<NA>
41304131<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중소기업제조기업글로벌 유망기업경기64.45224.6514.723.11.00.610.460.830.60.750.730.8572544407728085590기타문구베트남태국인도네시아
41314132<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중소기업수출중개기업(오퍼상,에이전트 등)글로벌 초보기업경남45.45219.49.4514.60.580.490.460.580.350.580.450.441146561610637519기타기계요소일본미국태국
41324133<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중소기업수출중개기업(오퍼상,에이전트 등)글로벌 유망기업광주55.55220.511.5521.50.580.610.440.750.40.920.50.81100000000500007290기타산업기계우즈베키스탄러시아일본
41334134<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중소기업제조기업글로벌 초보기업충북52.4221.5511.5517.30.750.670.370.670.460.580.450.74100000003000169기타농산가공품teatea bagherb tea