Overview

Dataset statistics

Number of variables12
Number of observations23
Missing cells41
Missing cells (%)14.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory112.7 B

Variable types

Text1
Numeric11

Dataset

Description한국외식업경기지수 조사결과(업종별, 지역별, 프렌차이즈별 등 동향)
Author농림축산식품부
URLhttps://www.data.go.kr/data/3076485/fileData.do

Alerts

빈도 (개) is highly overall correlated with 2013 4분기High correlation
2012 1분기 is highly overall correlated with 2012 2분기 and 3 other fieldsHigh correlation
2012 2분기 is highly overall correlated with 2012 1분기 and 3 other fieldsHigh correlation
2012 3분기 is highly overall correlated with 2013 1분기 and 1 other fieldsHigh correlation
2012 4분기 is highly overall correlated with 2012 1분기 and 1 other fieldsHigh correlation
2013 1분기 is highly overall correlated with 2012 1분기 and 4 other fieldsHigh correlation
2013 2분기 is highly overall correlated with 2012 1분기 and 2 other fieldsHigh correlation
2013 4분기 is highly overall correlated with 빈도 (개) and 2 other fieldsHigh correlation
2014 1분기 is highly overall correlated with 2014 2분기전망High correlation
2014 2분기전망 is highly overall correlated with 2014 1분기High correlation
빈도 (개) has 1 (4.3%) missing valuesMissing
2012 1분기 has 7 (30.4%) missing valuesMissing
2012 2분기 has 7 (30.4%) missing valuesMissing
2012 3분기 has 7 (30.4%) missing valuesMissing
2012 4분기 has 7 (30.4%) missing valuesMissing
2013 1분기 has 7 (30.4%) missing valuesMissing
2013 2분기 has 1 (4.3%) missing valuesMissing
2013 3분기 has 1 (4.3%) missing valuesMissing
2013 4분기 has 1 (4.3%) missing valuesMissing
2014 1분기 has 1 (4.3%) missing valuesMissing
2014 2분기전망 has 1 (4.3%) missing valuesMissing
구분 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:35:25.396737
Analysis finished2023-12-12 13:35:38.871964
Duration13.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T22:35:39.019504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length13
Mean length10.652174
Min length6

Characters and Unicode

Total characters245
Distinct characters68
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row한식_일반한식
2nd row한식_한정식
3rd row한식_해산물류전문점
4th row한식_육류구이(소)
5th row한식_육류구이(돼지)
ValueCountFrequency (%)
기타 5
 
17.2%
한식_일반한식 1
 
3.4%
외국식_서양식(이탈리아 1
 
3.4%
주점_기타주접업 1
 
3.4%
주점_유흥주접업 1
 
3.4%
음식점_분식및김밥전문점 1
 
3.4%
음식점_치킨전문점 1
 
3.4%
음식점_유사음식점업 1
 
3.4%
및 1
 
3.4%
음식점_피자·햄버거·샌드위치 1
 
3.4%
Other values (15) 15
51.7%
2023-12-12T22:35:39.405808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 31
 
12.7%
_ 22
 
9.0%
점 18
 
7.3%
한 14
 
5.7%
음 10
 
4.1%
타 9
 
3.7%
기 9
 
3.7%
류 8
 
3.3%
업 7
 
2.9%
) 7
 
2.9%
Other values (58) 110
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 197
80.4%
Connector Punctuation 22
 
9.0%
Space Separator 8
 
3.3%
Close Punctuation 7
 
2.9%
Open Punctuation 7
 
2.9%
Other Punctuation 4
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 31
 
15.7%
점 18
 
9.1%
한 14
 
7.1%
음 10
 
5.1%
타 9
 
4.6%
기 9
 
4.6%
류 8
 
4.1%
업 7
 
3.6%
이 6
 
3.0%
전 6
 
3.0%
Other values (52) 79
40.1%
Space Separator
ValueCountFrequency (%)
7
87.5%
　 1
 
12.5%
Connector Punctuation
ValueCountFrequency (%)
_ 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
· 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 197
80.4%
Common 48
 
19.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 31
 
15.7%
점 18
 
9.1%
한 14
 
7.1%
음 10
 
5.1%
타 9
 
4.6%
기 9
 
4.6%
류 8
 
4.1%
업 7
 
3.6%
이 6
 
3.0%
전 6
 
3.0%
Other values (52) 79
40.1%
Common
ValueCountFrequency (%)
_ 22
45.8%
) 7
 
14.6%
( 7
 
14.6%
7
 
14.6%
· 4
 
8.3%
　 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 197
80.4%
ASCII 43
 
17.6%
None 5
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 31
 
15.7%
점 18
 
9.1%
한 14
 
7.1%
음 10
 
5.1%
타 9
 
4.6%
기 9
 
4.6%
류 8
 
4.1%
업 7
 
3.6%
이 6
 
3.0%
전 6
 
3.0%
Other values (52) 79
40.1%
ASCII
ValueCountFrequency (%)
_ 22
51.2%
) 7
 
16.3%
( 7
 
16.3%
7
 
16.3%
None
ValueCountFrequency (%)
· 4
80.0%
　 1
 
20.0%

빈도 (개)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)100.0%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean135.81818
Minimum10
Maximum410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:39.523498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile17.25
Q136.25
median77.5
Q3225.25
95-th percentile350.9
Maximum410
Range400
Interquartile range (IQR)189

Descriptive statistics

Standard deviation120.10259
Coefficient of variation (CV)0.88428948
Kurtosis-0.21966402
Mean135.81818
Median Absolute Deviation (MAD)58.5
Skewness0.91288493
Sum2988
Variance14424.632
MonotonicityNot monotonic
2023-12-12T22:35:39.674699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
352 1
 
4.3%
61 1
 
4.3%
77 1
 
4.3%
330 1
 
4.3%
134 1
 
4.3%
190 1
 
4.3%
223 1
 
4.3%
46 1
 
4.3%
10 1
 
4.3%
17 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
10 1
4.3%
17 1
4.3%
22 1
4.3%
28 1
4.3%
32 1
4.3%
33 1
4.3%
46 1
4.3%
52 1
4.3%
61 1
4.3%
72 1
4.3%
ValueCountFrequency (%)
410 1
4.3%
352 1
4.3%
330 1
4.3%
229 1
4.3%
228 1
4.3%
226 1
4.3%
223 1
4.3%
190 1
4.3%
138 1
4.3%
134 1
4.3%

2012 1분기
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)100.0%
Missing7
Missing (%)30.4%
Infinite0
Infinite (%)0.0%
Mean102.45125
Minimum93.19
Maximum114.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:39.808694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum93.19
5-th percentile94.18
Q197.375
median101.99
Q3106.49
95-th percentile112.5175
Maximum114.79
Range21.6
Interquartile range (IQR)9.115

Descriptive statistics

Standard deviation6.6489146
Coefficient of variation (CV)0.064898326
Kurtosis-0.89657256
Mean102.45125
Median Absolute Deviation (MAD)4.7
Skewness0.43806385
Sum1639.22
Variance44.208065
MonotonicityNot monotonic
2023-12-12T22:35:39.941226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
110.94 1
 
4.3%
97.83 1
 
4.3%
97.12 1
 
4.3%
95.24 1
 
4.3%
103.44 1
 
4.3%
103.64 1
 
4.3%
100.0 1
 
4.3%
93.19 1
 
4.3%
111.76 1
 
4.3%
110.0 1
 
4.3%
Other values (6) 6
26.1%
(Missing) 7
30.4%
ValueCountFrequency (%)
93.19 1
4.3%
94.51 1
4.3%
95.24 1
4.3%
97.12 1
4.3%
97.46 1
4.3%
97.83 1
4.3%
100.0 1
4.3%
100.85 1
4.3%
103.13 1
4.3%
103.44 1
4.3%
ValueCountFrequency (%)
114.79 1
4.3%
111.76 1
4.3%
110.94 1
4.3%
110.0 1
4.3%
105.32 1
4.3%
103.64 1
4.3%
103.44 1
4.3%
103.13 1
4.3%
100.85 1
4.3%
100.0 1
4.3%

2012 2분기
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)100.0%
Missing7
Missing (%)30.4%
Infinite0
Infinite (%)0.0%
Mean101.35375
Minimum90.34
Maximum113.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:40.073761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum90.34
5-th percentile93.0475
Q197.525
median100.96
Q3103.825
95-th percentile112.35
Maximum113.04
Range22.7
Interquartile range (IQR)6.3

Descriptive statistics

Standard deviation6.0790173
Coefficient of variation (CV)0.059978218
Kurtosis0.10705904
Mean101.35375
Median Absolute Deviation (MAD)3.58
Skewness0.37789415
Sum1621.66
Variance36.954452
MonotonicityNot monotonic
2023-12-12T22:35:40.175001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
112.12 1
 
4.3%
96.67 1
 
4.3%
97.09 1
 
4.3%
90.34 1
 
4.3%
103.16 1
 
4.3%
103.29 1
 
4.3%
100.0 1
 
4.3%
93.95 1
 
4.3%
107.14 1
 
4.3%
101.92 1
 
4.3%
Other values (6) 6
26.1%
(Missing) 7
30.4%
ValueCountFrequency (%)
90.34 1
4.3%
93.95 1
4.3%
96.67 1
4.3%
97.09 1
4.3%
97.67 1
4.3%
98.84 1
4.3%
98.92 1
4.3%
100.0 1
4.3%
101.92 1
4.3%
102.08 1
4.3%
ValueCountFrequency (%)
113.04 1
4.3%
112.12 1
4.3%
107.14 1
4.3%
105.43 1
4.3%
103.29 1
4.3%
103.16 1
4.3%
102.08 1
4.3%
101.92 1
4.3%
100.0 1
4.3%
98.92 1
4.3%

2012 3분기
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)100.0%
Missing7
Missing (%)30.4%
Infinite0
Infinite (%)0.0%
Mean99.920625
Minimum84.23
Maximum116.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:40.261665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum84.23
5-th percentile90.8375
Q197.2
median99.855
Q3102.005
95-th percentile109.17
Maximum116.67
Range32.44
Interquartile range (IQR)4.805

Descriptive statistics

Standard deviation6.9047505
Coefficient of variation (CV)0.069102355
Kurtosis2.6760765
Mean99.920625
Median Absolute Deviation (MAD)2.675
Skewness0.20997904
Sum1598.73
Variance47.67558
MonotonicityNot monotonic
2023-12-12T22:35:40.356276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
103.85 1
 
4.3%
98.72 1
 
4.3%
95.05 1
 
4.3%
84.23 1
 
4.3%
100.65 1
 
4.3%
105.67 1
 
4.3%
106.67 1
 
4.3%
97.22 1
 
4.3%
116.67 1
 
4.3%
100.68 1
 
4.3%
Other values (6) 6
26.1%
(Missing) 7
30.4%
ValueCountFrequency (%)
84.23 1
4.3%
93.04 1
4.3%
95.05 1
4.3%
97.14 1
4.3%
97.22 1
4.3%
98.04 1
4.3%
98.72 1
4.3%
99.83 1
4.3%
99.88 1
4.3%
100.65 1
4.3%
ValueCountFrequency (%)
116.67 1
4.3%
106.67 1
4.3%
105.67 1
4.3%
103.85 1
4.3%
101.39 1
4.3%
100.68 1
4.3%
100.65 1
4.3%
99.88 1
4.3%
99.83 1
4.3%
98.72 1
4.3%

2012 4분기
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)100.0%
Missing7
Missing (%)30.4%
Infinite0
Infinite (%)0.0%
Mean99.42875
Minimum92.96
Maximum114.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:40.459172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum92.96
5-th percentile94.1375
Q195.2475
median97.74
Q3101.62
95-th percentile108.9275
Maximum114.29
Range21.33
Interquartile range (IQR)6.3725

Descriptive statistics

Standard deviation5.8624408
Coefficient of variation (CV)0.058961224
Kurtosis1.2756185
Mean99.42875
Median Absolute Deviation (MAD)2.67
Skewness1.2954429
Sum1590.86
Variance34.368212
MonotonicityNot monotonic
2023-12-12T22:35:40.563974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
114.29 1
 
4.3%
94.9 1
 
4.3%
95.34 1
 
4.3%
98.94 1
 
4.3%
95.24 1
 
4.3%
104.59 1
 
4.3%
99.11 1
 
4.3%
96.54 1
 
4.3%
107.14 1
 
4.3%
94.53 1
 
4.3%
Other values (6) 6
26.1%
(Missing) 7
30.4%
ValueCountFrequency (%)
92.96 1
4.3%
94.53 1
4.3%
94.9 1
4.3%
95.24 1
4.3%
95.25 1
4.3%
95.34 1
4.3%
95.71 1
4.3%
96.54 1
4.3%
98.94 1
4.3%
99.11 1
4.3%
ValueCountFrequency (%)
114.29 1
4.3%
107.14 1
4.3%
106.25 1
4.3%
104.59 1
4.3%
100.63 1
4.3%
99.44 1
4.3%
99.11 1
4.3%
98.94 1
4.3%
96.54 1
4.3%
95.71 1
4.3%

2013 1분기
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)100.0%
Missing7
Missing (%)30.4%
Infinite0
Infinite (%)0.0%
Mean100.03937
Minimum91.13
Maximum117.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:40.658980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum91.13
5-th percentile92.1575
Q195.4675
median97.905
Q3101.555
95-th percentile117.5375
Maximum117.65
Range26.52
Interquartile range (IQR)6.0875

Descriptive statistics

Standard deviation7.6335072
Coefficient of variation (CV)0.076305027
Kurtosis2.1898027
Mean100.03937
Median Absolute Deviation (MAD)3.105
Skewness1.58648
Sum1600.63
Variance58.270433
MonotonicityNot monotonic
2023-12-12T22:35:40.751269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
117.65 1
 
4.3%
96.81 1
 
4.3%
95.16 1
 
4.3%
91.13 1
 
4.3%
98.05 1
 
4.3%
102.05 1
 
4.3%
101.39 1
 
4.3%
97.65 1
 
4.3%
117.5 1
 
4.3%
100.58 1
 
4.3%
Other values (6) 6
26.1%
(Missing) 7
30.4%
ValueCountFrequency (%)
91.13 1
4.3%
92.5 1
4.3%
94.44 1
4.3%
95.16 1
4.3%
95.57 1
4.3%
96.81 1
4.3%
97.65 1
4.3%
97.76 1
4.3%
98.05 1
4.3%
98.59 1
4.3%
ValueCountFrequency (%)
117.65 1
4.3%
117.5 1
4.3%
103.8 1
4.3%
102.05 1
4.3%
101.39 1
4.3%
100.58 1
4.3%
98.59 1
4.3%
98.05 1
4.3%
97.76 1
4.3%
97.65 1
4.3%

2013 2분기
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)100.0%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean96.554091
Minimum83.94
Maximum107.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:40.845511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum83.94
5-th percentile88.2405
Q193.6025
median96.465
Q399.12
95-th percentile103.654
Maximum107.14
Range23.2
Interquartile range (IQR)5.5175

Descriptive statistics

Standard deviation5.3366421
Coefficient of variation (CV)0.05527101
Kurtosis0.51892046
Mean96.554091
Median Absolute Deviation (MAD)3
Skewness-0.2699031
Sum2124.19
Variance28.479749
MonotonicityNot monotonic
2023-12-12T22:35:40.938359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
95.24 1
 
4.3%
99.44 1
 
4.3%
97.62 1
 
4.3%
92.82 1
 
4.3%
83.94 1
 
4.3%
97.7 1
 
4.3%
96.5 1
 
4.3%
96.15 1
 
4.3%
102.78 1
 
4.3%
107.14 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
83.94 1
4.3%
88.1 1
4.3%
90.91 1
4.3%
91.94 1
4.3%
92.82 1
4.3%
93.44 1
4.3%
94.09 1
4.3%
95.24 1
4.3%
95.97 1
4.3%
96.15 1
4.3%
ValueCountFrequency (%)
107.14 1
4.3%
103.7 1
4.3%
102.78 1
4.3%
102.5 1
4.3%
102.11 1
4.3%
99.44 1
4.3%
98.16 1
4.3%
97.7 1
4.3%
97.62 1
4.3%
97.51 1
4.3%

2013 3분기
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)100.0%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean98.596364
Minimum85.89
Maximum108.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:41.025544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum85.89
5-th percentile87.5535
Q196.73
median99.535
Q3101.1875
95-th percentile106.2405
Maximum108.82
Range22.93
Interquartile range (IQR)4.4575

Descriptive statistics

Standard deviation5.8921445
Coefficient of variation (CV)0.059760262
Kurtosis0.29444476
Mean98.596364
Median Absolute Deviation (MAD)1.8
Skewness-0.62193729
Sum2169.12
Variance34.717367
MonotonicityNot monotonic
2023-12-12T22:35:41.115326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
99.07 1
 
4.3%
100.65 1
 
4.3%
104.81 1
 
4.3%
101.06 1
 
4.3%
85.89 1
 
4.3%
100.26 1
 
4.3%
101.29 1
 
4.3%
94.83 1
 
4.3%
108.82 1
 
4.3%
87.5 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
85.89 1
4.3%
87.5 1
4.3%
88.57 1
4.3%
92.86 1
4.3%
94.83 1
4.3%
96.41 1
4.3%
97.69 1
4.3%
98.25 1
4.3%
98.47 1
4.3%
98.49 1
4.3%
ValueCountFrequency (%)
108.82 1
4.3%
106.25 1
4.3%
106.06 1
4.3%
104.81 1
4.3%
101.29 1
4.3%
101.23 1
4.3%
101.06 1
4.3%
100.66 1
4.3%
100.65 1
4.3%
100.26 1
4.3%

2013 4분기
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)95.5%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean101.01591
Minimum93.35
Maximum114.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:41.208153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum93.35
5-th percentile93.765
Q197.8675
median100
Q3103.1725
95-th percentile110.496
Maximum114.29
Range20.94
Interquartile range (IQR)5.305

Descriptive statistics

Standard deviation5.3142877
Coefficient of variation (CV)0.052608423
Kurtosis0.67116232
Mean101.01591
Median Absolute Deviation (MAD)2.34
Skewness0.9274406
Sum2222.35
Variance28.241654
MonotonicityNot monotonic
2023-12-12T22:35:41.644993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
100.0 2
 
8.7%
97.06 1
 
4.3%
97.46 1
 
4.3%
100.89 1
 
4.3%
100.86 1
 
4.3%
95.0 1
 
4.3%
98.94 1
 
4.3%
101.01 1
 
4.3%
105.21 1
 
4.3%
114.29 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
93.35 1
4.3%
93.7 1
4.3%
95.0 1
4.3%
97.06 1
4.3%
97.46 1
4.3%
97.86 1
4.3%
97.89 1
4.3%
98.89 1
4.3%
98.94 1
4.3%
99.11 1
4.3%
ValueCountFrequency (%)
114.29 1
4.3%
110.61 1
4.3%
108.33 1
4.3%
106.9 1
4.3%
105.21 1
4.3%
103.85 1
4.3%
101.14 1
4.3%
101.01 1
4.3%
100.89 1
4.3%
100.86 1
4.3%

2014 1분기
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)100.0%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean97.558182
Minimum86.19
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:41.766665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.19
5-th percentile88.7535
Q194.88
median97.295
Q3100.975
95-th percentile109.058
Maximum110
Range23.81
Interquartile range (IQR)6.095

Descriptive statistics

Standard deviation5.772817
Coefficient of variation (CV)0.059173068
Kurtosis0.63892965
Mean97.558182
Median Absolute Deviation (MAD)2.73
Skewness0.30346172
Sum2146.28
Variance33.325416
MonotonicityNot monotonic
2023-12-12T22:35:41.901784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
95.6 1
 
4.3%
98.36 1
 
4.3%
101.3 1
 
4.3%
96.06 1
 
4.3%
86.19 1
 
4.3%
101.32 1
 
4.3%
97.53 1
 
4.3%
96.74 1
 
4.3%
110.0 1
 
4.3%
102.94 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
86.19 1
4.3%
88.64 1
4.3%
90.91 1
4.3%
90.97 1
4.3%
94.54 1
4.3%
94.64 1
4.3%
95.6 1
4.3%
96.06 1
4.3%
96.46 1
4.3%
96.74 1
4.3%
ValueCountFrequency (%)
110.0 1
4.3%
109.38 1
4.3%
102.94 1
4.3%
101.92 1
4.3%
101.32 1
4.3%
101.3 1
4.3%
100.0 1
4.3%
98.36 1
4.3%
98.19 1
4.3%
97.53 1
4.3%

2014 2분기전망
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)100.0%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean96.643182
Minimum86.36
Maximum110.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T22:35:42.034948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86.36
5-th percentile87.9235
Q193.985
median95.75
Q398.905
95-th percentile104.935
Maximum110.94
Range24.58
Interquartile range (IQR)4.92

Descriptive statistics

Standard deviation5.437991
Coefficient of variation (CV)0.05626875
Kurtosis1.4742807
Mean96.643182
Median Absolute Deviation (MAD)1.85
Skewness0.67238356
Sum2126.15
Variance29.571747
MonotonicityNot monotonic
2023-12-12T22:35:42.151051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
95.74 1
 
4.3%
97.54 1
 
4.3%
97.4 1
 
4.3%
95.76 1
 
4.3%
87.69 1
 
4.3%
103.7 1
 
4.3%
96.64 1
 
4.3%
93.48 1
 
4.3%
105.0 1
 
4.3%
94.12 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
86.36 1
4.3%
87.69 1
4.3%
92.36 1
4.3%
93.48 1
4.3%
93.86 1
4.3%
93.94 1
4.3%
94.12 1
4.3%
94.3 1
4.3%
94.44 1
4.3%
95.62 1
4.3%
ValueCountFrequency (%)
110.94 1
4.3%
105.0 1
4.3%
103.7 1
4.3%
101.92 1
4.3%
100.0 1
4.3%
99.36 1
4.3%
97.54 1
4.3%
97.4 1
4.3%
96.64 1
4.3%
95.98 1
4.3%

Interactions

2023-12-12T22:35:37.109894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:25.790406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:26.945493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:28.290607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:29.493893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.647017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.506690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:32.447846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:33.573997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:34.664811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.991207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:37.220325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:25.904098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:27.054967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:28.414305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:29.612186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.747453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.588030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:32.557500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:33.693286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.078510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:36.106962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:37.329234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:26.003442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:27.134913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:28.517996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:29.714044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.834636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.660091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:32.642790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:33.793918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.151443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:36.206202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:37.427180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:26.100597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:27.216119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:28.624247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:29.815878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.909354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.732647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:32.730228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:33.889843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.240379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:36.291328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:37.542345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:26.206338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:27.299714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:28.756539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:29.935190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.989682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.812287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:32.851007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:33.992326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.345296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:36.396910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:37.677210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:26.309718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:27.380809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:28.863616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.025433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.063911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.905066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:32.977372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:34.090271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.419838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:36.492982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:37.782534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:26.419845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:27.499902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:28.968361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.120919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.140442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.985805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:33.091367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:34.186157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.504625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:36.597400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:37.877569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:26.514612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:27.615286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:29.086316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.241484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.223257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:32.077543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:33.176689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:34.266916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.593025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:36.694367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:37.959831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:26.605420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:27.986581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:29.185199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.339679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.288591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:32.156544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:33.274616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:34.349261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.685885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:36.790878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:38.056050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:26.713898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:28.077713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:29.275544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.429374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.356777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:32.250883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:33.369348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:34.460810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.776556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:36.893030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:38.158581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:26.843533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:28.186595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:29.380864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:30.529877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:31.428229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:32.347382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:33.465815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:34.570865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:35.877200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:35:37.000241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:35:42.249563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분빈도 (개)2012 1분기2012 2분기2012 3분기2012 4분기2013 1분기2013 2분기2013 3분기2013 4분기2014 1분기2014 2분기전망
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
빈도 (개)1.0001.0000.0000.1970.4640.0000.6800.0000.0000.0000.2940.000
2012 1분기1.0000.0001.0000.8150.3570.2970.7910.5970.6360.0000.0000.000
2012 2분기1.0000.1970.8151.0000.7660.3370.4080.5110.6980.8400.5930.000
2012 3분기1.0000.4640.3570.7661.0000.7560.7210.6900.7470.7080.7640.000
2012 4분기1.0000.0000.2970.3370.7561.0000.6150.2890.7810.8870.7110.211
2013 1분기1.0000.6800.7910.4080.7210.6151.0000.7570.6380.2240.6010.000
2013 2분기1.0000.0000.5970.5110.6900.2890.7571.0000.7400.6700.9410.307
2013 3분기1.0000.0000.6360.6980.7470.7810.6380.7401.0000.3440.7330.693
2013 4분기1.0000.0000.0000.8400.7080.8870.2240.6700.3441.0000.6090.000
2014 1분기1.0000.2940.0000.5930.7640.7110.6010.9410.7330.6091.0000.478
2014 2분기전망1.0000.0000.0000.0000.0000.2110.0000.3070.6930.0000.4781.000
2023-12-12T22:35:42.451329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
빈도 (개)2012 1분기2012 2분기2012 3분기2012 4분기2013 1분기2013 2분기2013 3분기2013 4분기2014 1분기2014 2분기전망
빈도 (개)1.000-0.309-0.379-0.485-0.312-0.118-0.285-0.065-0.637-0.229-0.100
2012 1분기-0.3091.0000.9030.2850.5440.7180.6530.2910.4470.097-0.035
2012 2분기-0.3790.9031.0000.3680.6060.6590.7320.2210.4530.1320.109
2012 3분기-0.4850.2850.3681.0000.1030.5850.4740.3940.7180.3120.150
2012 4분기-0.3120.5440.6060.1031.0000.4760.2560.2120.203-0.309-0.250
2013 1분기-0.1180.7180.6590.5850.4761.0000.6030.4680.6030.1440.012
2013 2분기-0.2850.6530.7320.4740.2560.6031.0000.2600.4220.3530.136
2013 3분기-0.0650.2910.2210.3940.2120.4680.2601.0000.3370.1290.404
2013 4분기-0.6370.4470.4530.7180.2030.6030.4220.3371.0000.0780.033
2014 1분기-0.2290.0970.1320.312-0.3090.1440.3530.1290.0781.0000.729
2014 2분기전망-0.100-0.0350.1090.150-0.2500.0120.1360.4040.0330.7291.000

Missing values

2023-12-12T22:35:38.316617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:35:38.551560image/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.
2023-12-12T22:35:38.741127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분빈도 (개)2012 1분기2012 2분기2012 3분기2012 4분기2013 1분기2013 2분기2013 3분기2013 4분기2014 1분기2014 2분기전망
0한식_일반한식35293.1993.9597.2296.5497.6595.2499.0797.0695.695.74
1한식_한정식22111.76107.14116.67107.14117.5103.7106.25108.3388.6486.36
2한식_해산물류전문점229114.79113.0493.04100.63103.8102.596.4198.8994.5494.3
3한식_육류구이(소)228<NA><NA><NA><NA><NA>97.5198.2599.1197.1593.86
4한식_육류구이(돼지)226<NA><NA><NA><NA><NA>94.0998.4993.3596.4694.44
5한식_육류구이(닭)28<NA><NA><NA><NA><NA>96.43106.06110.6194.64100.0
6한식_육류구이(오리)33<NA><NA><NA><NA><NA>91.94100.0106.990.9193.94
7한식_육류구이(기타)5294.5198.92101.3992.9692.5102.1197.69100.0100.0101.92
8한식_탕류·전골·찌개41097.4697.6799.8895.7198.5995.97100.6697.8697.4495.98
9한식_면류전문점78100.8598.8499.8395.2597.7693.44101.2393.7101.9299.36
구분빈도 (개)2012 1분기2012 2분기2012 3분기2012 4분기2013 1분기2013 2분기2013 3분기2013 4분기2014 1분기2014 2분기전망
13외국식_서양식(이탈리아)32<NA><NA><NA><NA><NA>90.9192.86100.0109.38110.94
14외국식_음식점업(기타)17<NA><NA><NA><NA><NA>107.1487.5103.85102.9494.12
15기타 음식점_제과점업10110.94112.12103.85114.29117.65102.78108.82114.29110.0105.0
16기타 음식점_피자·햄버거·샌드위치 및46100.0100.0106.6799.11101.3996.1594.83105.2196.7493.48
17기타 음식점_유사음식점업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18기타 음식점_치킨전문점223103.64103.29105.67104.59102.0596.5101.29101.0197.5396.64
19기타 음식점_분식및김밥전문점190103.44103.16100.6595.2498.0597.7100.2698.94101.32103.7
20주점_유흥주접업13495.2490.3484.2398.9491.1383.9485.8995.086.1987.69
21주점_기타주접업33097.1297.0995.0595.3495.1692.82101.06100.8696.0695.76
22비알콜음료점7797.8396.6798.7294.996.8197.62104.81100.89101.397.4