Overview

Dataset statistics

Number of variables20
Number of observations409
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory71.6 KiB
Average record size in memory179.3 B

Variable types

Numeric15
Categorical5

Dataset

Description년월,기관/유형,한국어,영어,일본어,중국어,베트남어,타갈로그어,몽골어,프랑스어,러시아어,우즈벡어,태국어,네팔어,인도네시아어,파키스탄어(우르두어),아랍어,스페인어,기타언어,합계
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15736/S/1/datasetView.do

Alerts

파키스탄어(우르두어) has constant value ""Constant
한국어 is highly overall correlated with 영어 and 10 other fieldsHigh correlation
영어 is highly overall correlated with 한국어 and 12 other fieldsHigh correlation
일본어 is highly overall correlated with 한국어 and 12 other fieldsHigh correlation
중국어 is highly overall correlated with 한국어 and 12 other fieldsHigh correlation
베트남어 is highly overall correlated with 한국어 and 14 other fieldsHigh correlation
타갈로그어 is highly overall correlated with 한국어 and 12 other fieldsHigh correlation
몽골어 is highly overall correlated with 한국어 and 12 other fieldsHigh correlation
러시아어 is highly overall correlated with 한국어 and 12 other fieldsHigh correlation
우즈벡어 is highly overall correlated with 한국어 and 12 other fieldsHigh correlation
태국어 is highly overall correlated with 영어 and 11 other fieldsHigh correlation
인도네시아어 is highly overall correlated with 한국어 and 12 other fieldsHigh correlation
아랍어 is highly overall correlated with 영어 and 11 other fieldsHigh correlation
스페인어 is highly overall correlated with 한국어 and 12 other fieldsHigh correlation
합계 is highly overall correlated with 한국어 and 12 other fieldsHigh correlation
네팔어 is highly overall correlated with 베트남어 and 1 other fieldsHigh correlation
기타언어 is highly overall correlated with 베트남어 and 1 other fieldsHigh correlation
프랑스어 is highly imbalanced (97.5%)Imbalance
네팔어 is highly imbalanced (95.5%)Imbalance
기타언어 is highly imbalanced (94.5%)Imbalance
한국어 has 244 (59.7%) zerosZeros
영어 has 199 (48.7%) zerosZeros
일본어 has 250 (61.1%) zerosZeros
중국어 has 281 (68.7%) zerosZeros
베트남어 has 288 (70.4%) zerosZeros
타갈로그어 has 269 (65.8%) zerosZeros
몽골어 has 289 (70.7%) zerosZeros
러시아어 has 285 (69.7%) zerosZeros
우즈벡어 has 299 (73.1%) zerosZeros
태국어 has 277 (67.7%) zerosZeros
인도네시아어 has 313 (76.5%) zerosZeros
아랍어 has 309 (75.6%) zerosZeros
스페인어 has 222 (54.3%) zerosZeros
합계 has 162 (39.6%) zerosZeros

Reproduction

Analysis started2024-05-17 22:51:40.750646
Analysis finished2024-05-17 22:53:03.266134
Duration1 minute and 22.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년월
Real number (ℝ)

Distinct58
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202163.72
Minimum201907
Maximum202404
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:03.564022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201907
5-th percentile201910
Q1202012
median202202
Q3202304
95-th percentile202402
Maximum202404
Range497
Interquartile range (IQR)292

Descriptive statistics

Standard deviation142.88217
Coefficient of variation (CV)0.00070676464
Kurtosis-0.99418798
Mean202163.72
Median Absolute Deviation (MAD)102
Skewness-0.13895374
Sum82684962
Variance20415.314
MonotonicityDecreasing
2024-05-18T07:53:04.019610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202404 8
 
2.0%
202305 8
 
2.0%
202207 8
 
2.0%
202208 8
 
2.0%
202209 8
 
2.0%
202210 8
 
2.0%
202211 8
 
2.0%
202212 8
 
2.0%
202302 8
 
2.0%
202303 8
 
2.0%
Other values (48) 329
80.4%
ValueCountFrequency (%)
201907 6
1.5%
201908 6
1.5%
201909 6
1.5%
201910 6
1.5%
201911 6
1.5%
201912 6
1.5%
202001 6
1.5%
202002 6
1.5%
202003 6
1.5%
202004 6
1.5%
ValueCountFrequency (%)
202404 8
2.0%
202403 8
2.0%
202402 8
2.0%
202401 8
2.0%
202312 8
2.0%
202311 8
2.0%
202310 8
2.0%
202309 8
2.0%
202308 8
2.0%
202307 8
2.0%

기관/유형
Categorical

Distinct9
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
방문
58 
이동상담
58 
이메일
58 
전화
58 
화상상담
58 
Other values (4)
119 

Length

Max length4
Median length3
Mean length2.992665
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSNS
2nd row게시판
3rd row문자
4th row방문
5th row이동상담

Common Values

ValueCountFrequency (%)
방문 58
14.2%
이동상담 58
14.2%
이메일 58
14.2%
전화 58
14.2%
화상상담 58
14.2%
SNS 39
9.5%
게시판 39
9.5%
문자 22
 
5.4%
홈페이지 19
 
4.6%

Length

2024-05-18T07:53:04.486824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:53:04.886115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
방문 58
14.2%
이동상담 58
14.2%
이메일 58
14.2%
전화 58
14.2%
화상상담 58
14.2%
sns 39
9.5%
게시판 39
9.5%
문자 22
 
5.4%
홈페이지 19
 
4.6%

한국어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct61
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.669927
Minimum0
Maximum483
Zeros244
Zeros (%)59.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:05.471223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39
95-th percentile52.6
Maximum483
Range483
Interquartile range (IQR)9

Descriptive statistics

Standard deviation30.883654
Coefficient of variation (CV)2.894458
Kurtosis136.28691
Mean10.669927
Median Absolute Deviation (MAD)0
Skewness9.6969223
Sum4364
Variance953.8001
MonotonicityNot monotonic
2024-05-18T07:53:05.915428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 244
59.7%
1 18
 
4.4%
2 9
 
2.2%
3 7
 
1.7%
17 7
 
1.7%
7 6
 
1.5%
16 6
 
1.5%
6 6
 
1.5%
4 6
 
1.5%
8 5
 
1.2%
Other values (51) 95
 
23.2%
ValueCountFrequency (%)
0 244
59.7%
1 18
 
4.4%
2 9
 
2.2%
3 7
 
1.7%
4 6
 
1.5%
5 3
 
0.7%
6 6
 
1.5%
7 6
 
1.5%
8 5
 
1.2%
9 3
 
0.7%
ValueCountFrequency (%)
483 1
0.2%
173 1
0.2%
111 2
0.5%
99 1
0.2%
93 1
0.2%
81 1
0.2%
75 1
0.2%
73 2
0.5%
70 1
0.2%
68 2
0.5%

영어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct117
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.870416
Minimum0
Maximum612
Zeros199
Zeros (%)48.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:06.332586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q348
95-th percentile253
Maximum612
Range612
Interquartile range (IQR)48

Descriptive statistics

Standard deviation90.278655
Coefficient of variation (CV)1.926133
Kurtosis8.8468834
Mean46.870416
Median Absolute Deviation (MAD)1
Skewness2.720347
Sum19170
Variance8150.2356
MonotonicityNot monotonic
2024-05-18T07:53:06.814824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 199
48.7%
1 15
 
3.7%
2 13
 
3.2%
3 7
 
1.7%
4 6
 
1.5%
86 5
 
1.2%
32 4
 
1.0%
60 4
 
1.0%
22 4
 
1.0%
35 3
 
0.7%
Other values (107) 149
36.4%
ValueCountFrequency (%)
0 199
48.7%
1 15
 
3.7%
2 13
 
3.2%
3 7
 
1.7%
4 6
 
1.5%
5 2
 
0.5%
6 1
 
0.2%
7 2
 
0.5%
9 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
612 1
0.2%
567 1
0.2%
499 1
0.2%
356 1
0.2%
347 1
0.2%
345 1
0.2%
324 1
0.2%
313 2
0.5%
311 1
0.2%
308 1
0.2%

일본어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct57
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.105134
Minimum0
Maximum180
Zeros250
Zeros (%)61.1%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:07.442420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39
95-th percentile62.2
Maximum180
Range180
Interquartile range (IQR)9

Descriptive statistics

Standard deviation21.465229
Coefficient of variation (CV)2.1241904
Kurtosis12.250914
Mean10.105134
Median Absolute Deviation (MAD)0
Skewness2.9991157
Sum4133
Variance460.75608
MonotonicityNot monotonic
2024-05-18T07:53:07.896135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 250
61.1%
1 19
 
4.6%
2 13
 
3.2%
66 6
 
1.5%
3 6
 
1.5%
17 6
 
1.5%
18 6
 
1.5%
15 5
 
1.2%
4 5
 
1.2%
10 4
 
1.0%
Other values (47) 89
 
21.8%
ValueCountFrequency (%)
0 250
61.1%
1 19
 
4.6%
2 13
 
3.2%
3 6
 
1.5%
4 5
 
1.2%
5 2
 
0.5%
6 2
 
0.5%
7 4
 
1.0%
8 2
 
0.5%
9 4
 
1.0%
ValueCountFrequency (%)
180 1
 
0.2%
104 1
 
0.2%
101 1
 
0.2%
82 1
 
0.2%
79 3
0.7%
75 1
 
0.2%
72 1
 
0.2%
68 1
 
0.2%
66 6
1.5%
65 2
 
0.5%

중국어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct96
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.266504
Minimum0
Maximum558
Zeros281
Zeros (%)68.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:08.202297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q316
95-th percentile190.2
Maximum558
Range558
Interquartile range (IQR)16

Descriptive statistics

Standard deviation71.548385
Coefficient of variation (CV)2.4447193
Kurtosis17.723659
Mean29.266504
Median Absolute Deviation (MAD)0
Skewness3.7197047
Sum11970
Variance5119.1714
MonotonicityNot monotonic
2024-05-18T07:53:08.512015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 281
68.7%
1 11
 
2.7%
25 3
 
0.7%
26 3
 
0.7%
191 3
 
0.7%
2 3
 
0.7%
29 3
 
0.7%
3 3
 
0.7%
64 2
 
0.5%
35 2
 
0.5%
Other values (86) 95
 
23.2%
ValueCountFrequency (%)
0 281
68.7%
1 11
 
2.7%
2 3
 
0.7%
3 3
 
0.7%
4 1
 
0.2%
5 1
 
0.2%
6 2
 
0.5%
9 1
 
0.2%
10 1
 
0.2%
11 1
 
0.2%
ValueCountFrequency (%)
558 1
0.2%
489 1
0.2%
460 1
0.2%
454 1
0.2%
274 1
0.2%
254 1
0.2%
253 1
0.2%
240 1
0.2%
233 1
0.2%
231 1
0.2%

베트남어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct69
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.462103
Minimum0
Maximum358
Zeros288
Zeros (%)70.4%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:08.930511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile213
Maximum358
Range358
Interquartile range (IQR)3

Descriptive statistics

Standard deviation72.112923
Coefficient of variation (CV)2.6259068
Kurtosis6.118548
Mean27.462103
Median Absolute Deviation (MAD)0
Skewness2.7097885
Sum11232
Variance5200.2737
MonotonicityNot monotonic
2024-05-18T07:53:09.384486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 288
70.4%
2 9
 
2.2%
1 7
 
1.7%
25 5
 
1.2%
17 5
 
1.2%
3 5
 
1.2%
6 4
 
1.0%
18 4
 
1.0%
28 4
 
1.0%
19 3
 
0.7%
Other values (59) 75
 
18.3%
ValueCountFrequency (%)
0 288
70.4%
1 7
 
1.7%
2 9
 
2.2%
3 5
 
1.2%
4 2
 
0.5%
5 3
 
0.7%
6 4
 
1.0%
7 3
 
0.7%
9 2
 
0.5%
11 2
 
0.5%
ValueCountFrequency (%)
358 1
0.2%
339 1
0.2%
327 1
0.2%
306 1
0.2%
305 1
0.2%
303 1
0.2%
270 1
0.2%
269 1
0.2%
264 1
0.2%
261 1
0.2%

타갈로그어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct99
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.836186
Minimum0
Maximum353
Zeros269
Zeros (%)65.8%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:09.812433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q329
95-th percentile218
Maximum353
Range353
Interquartile range (IQR)29

Descriptive statistics

Standard deviation74.118083
Coefficient of variation (CV)2.068247
Kurtosis4.2594825
Mean35.836186
Median Absolute Deviation (MAD)0
Skewness2.2545239
Sum14657
Variance5493.4903
MonotonicityNot monotonic
2024-05-18T07:53:10.344992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 269
65.8%
1 10
 
2.4%
2 6
 
1.5%
233 3
 
0.7%
23 3
 
0.7%
136 3
 
0.7%
44 3
 
0.7%
34 3
 
0.7%
101 2
 
0.5%
83 2
 
0.5%
Other values (89) 105
 
25.7%
ValueCountFrequency (%)
0 269
65.8%
1 10
 
2.4%
2 6
 
1.5%
3 1
 
0.2%
5 2
 
0.5%
6 2
 
0.5%
11 1
 
0.2%
12 1
 
0.2%
14 1
 
0.2%
15 1
 
0.2%
ValueCountFrequency (%)
353 1
0.2%
328 1
0.2%
313 1
0.2%
308 1
0.2%
306 1
0.2%
305 1
0.2%
286 1
0.2%
285 1
0.2%
281 1
0.2%
271 1
0.2%

몽골어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct74
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.520782
Minimum0
Maximum464
Zeros289
Zeros (%)70.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:10.671214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile143.4
Maximum464
Range464
Interquartile range (IQR)1

Descriptive statistics

Standard deviation61.991264
Coefficient of variation (CV)2.5281112
Kurtosis20.16672
Mean24.520782
Median Absolute Deviation (MAD)0
Skewness3.9548574
Sum10029
Variance3842.9168
MonotonicityNot monotonic
2024-05-18T07:53:10.929441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 289
70.7%
1 20
 
4.9%
2 4
 
1.0%
75 3
 
0.7%
98 3
 
0.7%
72 3
 
0.7%
67 2
 
0.5%
117 2
 
0.5%
145 2
 
0.5%
238 2
 
0.5%
Other values (64) 79
 
19.3%
ValueCountFrequency (%)
0 289
70.7%
1 20
 
4.9%
2 4
 
1.0%
3 2
 
0.5%
4 1
 
0.2%
5 1
 
0.2%
7 2
 
0.5%
14 1
 
0.2%
19 1
 
0.2%
26 2
 
0.5%
ValueCountFrequency (%)
464 1
0.2%
456 1
0.2%
429 1
0.2%
413 1
0.2%
254 1
0.2%
238 2
0.5%
234 1
0.2%
208 1
0.2%
199 1
0.2%
180 1
0.2%

프랑스어
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
0
408 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 408
99.8%
1 1
 
0.2%

Length

2024-05-18T07:53:11.160010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:53:11.383802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 408
99.8%
1 1
 
0.2%

러시아어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct80
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.254279
Minimum0
Maximum645
Zeros285
Zeros (%)69.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:11.706655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile366.8
Maximum645
Range645
Interquartile range (IQR)7

Descriptive statistics

Standard deviation126.31376
Coefficient of variation (CV)2.7308557
Kurtosis7.8744736
Mean46.254279
Median Absolute Deviation (MAD)0
Skewness2.9452945
Sum18918
Variance15955.166
MonotonicityNot monotonic
2024-05-18T07:53:12.140931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 285
69.7%
1 13
 
3.2%
13 7
 
1.7%
8 5
 
1.2%
7 5
 
1.2%
10 4
 
1.0%
12 4
 
1.0%
22 3
 
0.7%
14 3
 
0.7%
16 3
 
0.7%
Other values (70) 77
 
18.8%
ValueCountFrequency (%)
0 285
69.7%
1 13
 
3.2%
3 2
 
0.5%
4 1
 
0.2%
5 1
 
0.2%
6 2
 
0.5%
7 5
 
1.2%
8 5
 
1.2%
9 3
 
0.7%
10 4
 
1.0%
ValueCountFrequency (%)
645 1
0.2%
616 1
0.2%
597 1
0.2%
586 1
0.2%
576 1
0.2%
569 1
0.2%
560 1
0.2%
555 1
0.2%
541 1
0.2%
494 1
0.2%

우즈벡어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct63
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.349633
Minimum0
Maximum457
Zeros299
Zeros (%)73.1%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:12.555632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile233
Maximum457
Range457
Interquartile range (IQR)1

Descriptive statistics

Standard deviation80.165683
Coefficient of variation (CV)2.8277503
Kurtosis7.9817829
Mean28.349633
Median Absolute Deviation (MAD)0
Skewness2.9579086
Sum11595
Variance6426.5368
MonotonicityNot monotonic
2024-05-18T07:53:12.941163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 299
73.1%
1 12
 
2.9%
5 12
 
2.9%
9 4
 
1.0%
7 4
 
1.0%
6 4
 
1.0%
14 3
 
0.7%
3 3
 
0.7%
4 3
 
0.7%
11 3
 
0.7%
Other values (53) 62
 
15.2%
ValueCountFrequency (%)
0 299
73.1%
1 12
 
2.9%
2 1
 
0.2%
3 3
 
0.7%
4 3
 
0.7%
5 12
 
2.9%
6 4
 
1.0%
7 4
 
1.0%
8 3
 
0.7%
9 4
 
1.0%
ValueCountFrequency (%)
457 1
0.2%
404 1
0.2%
379 1
0.2%
369 2
0.5%
332 1
0.2%
325 1
0.2%
310 1
0.2%
301 1
0.2%
295 1
0.2%
289 1
0.2%

태국어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct78
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.449878
Minimum0
Maximum566
Zeros277
Zeros (%)67.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:13.257400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile170.8
Maximum566
Range566
Interquartile range (IQR)4

Descriptive statistics

Standard deviation63.8754
Coefficient of variation (CV)2.509851
Kurtosis16.347328
Mean25.449878
Median Absolute Deviation (MAD)0
Skewness3.4692447
Sum10409
Variance4080.0667
MonotonicityNot monotonic
2024-05-18T07:53:13.854566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 277
67.7%
1 14
 
3.4%
2 8
 
2.0%
3 7
 
1.7%
5 5
 
1.2%
8 4
 
1.0%
12 3
 
0.7%
161 3
 
0.7%
115 3
 
0.7%
9 2
 
0.5%
Other values (68) 83
 
20.3%
ValueCountFrequency (%)
0 277
67.7%
1 14
 
3.4%
2 8
 
2.0%
3 7
 
1.7%
4 2
 
0.5%
5 5
 
1.2%
6 2
 
0.5%
7 2
 
0.5%
8 4
 
1.0%
9 2
 
0.5%
ValueCountFrequency (%)
566 1
0.2%
337 1
0.2%
277 1
0.2%
275 1
0.2%
267 1
0.2%
258 1
0.2%
241 1
0.2%
233 1
0.2%
226 1
0.2%
216 1
0.2%

네팔어
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
0
407 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 407
99.5%
1 2
 
0.5%

Length

2024-05-18T07:53:14.260725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:53:14.576802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 407
99.5%
1 2
 
0.5%

인도네시아어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4938875
Minimum0
Maximum52
Zeros313
Zeros (%)76.5%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:14.918223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile19.6
Maximum52
Range52
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.0690285
Coefficient of variation (CV)2.8345418
Kurtosis13.645121
Mean2.4938875
Median Absolute Deviation (MAD)0
Skewness3.5639616
Sum1020
Variance49.971164
MonotonicityNot monotonic
2024-05-18T07:53:15.302584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 313
76.5%
1 20
 
4.9%
3 12
 
2.9%
2 9
 
2.2%
5 6
 
1.5%
24 4
 
1.0%
16 4
 
1.0%
6 4
 
1.0%
7 3
 
0.7%
20 3
 
0.7%
Other values (20) 31
 
7.6%
ValueCountFrequency (%)
0 313
76.5%
1 20
 
4.9%
2 9
 
2.2%
3 12
 
2.9%
4 3
 
0.7%
5 6
 
1.5%
6 4
 
1.0%
7 3
 
0.7%
8 1
 
0.2%
9 1
 
0.2%
ValueCountFrequency (%)
52 1
0.2%
38 2
0.5%
35 1
0.2%
34 1
0.2%
31 2
0.5%
30 1
0.2%
28 1
0.2%
27 2
0.5%
26 1
0.2%
25 1
0.2%

파키스탄어(우르두어)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
0
409 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 409
100.0%

Length

2024-05-18T07:53:15.708855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:53:16.017985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 409
100.0%

아랍어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6919315
Minimum0
Maximum74
Zeros309
Zeros (%)75.6%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:16.313220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile17.6
Maximum74
Range74
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.3185876
Coefficient of variation (CV)2.7187124
Kurtosis27.01704
Mean2.6919315
Median Absolute Deviation (MAD)0
Skewness4.3437671
Sum1101
Variance53.561724
MonotonicityNot monotonic
2024-05-18T07:53:16.703669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 309
75.6%
1 18
 
4.4%
4 7
 
1.7%
9 6
 
1.5%
2 6
 
1.5%
10 5
 
1.2%
16 5
 
1.2%
8 5
 
1.2%
3 5
 
1.2%
5 4
 
1.0%
Other values (21) 39
 
9.5%
ValueCountFrequency (%)
0 309
75.6%
1 18
 
4.4%
2 6
 
1.5%
3 5
 
1.2%
4 7
 
1.7%
5 4
 
1.0%
6 3
 
0.7%
7 4
 
1.0%
8 5
 
1.2%
9 6
 
1.5%
ValueCountFrequency (%)
74 1
0.2%
37 1
0.2%
35 1
0.2%
34 2
0.5%
32 1
0.2%
31 1
0.2%
29 2
0.5%
27 1
0.2%
26 1
0.2%
24 1
0.2%

스페인어
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6797066
Minimum0
Maximum23
Zeros222
Zeros (%)54.3%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:17.164424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile13
Maximum23
Range23
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.4899238
Coefficient of variation (CV)1.6755281
Kurtosis4.1628513
Mean2.6797066
Median Absolute Deviation (MAD)0
Skewness2.1010435
Sum1096
Variance20.159416
MonotonicityNot monotonic
2024-05-18T07:53:17.590210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 222
54.3%
1 38
 
9.3%
3 29
 
7.1%
4 19
 
4.6%
2 15
 
3.7%
8 12
 
2.9%
6 12
 
2.9%
5 11
 
2.7%
7 11
 
2.7%
11 7
 
1.7%
Other values (12) 33
 
8.1%
ValueCountFrequency (%)
0 222
54.3%
1 38
 
9.3%
2 15
 
3.7%
3 29
 
7.1%
4 19
 
4.6%
5 11
 
2.7%
6 12
 
2.9%
7 11
 
2.7%
8 12
 
2.9%
9 2
 
0.5%
ValueCountFrequency (%)
23 1
 
0.2%
21 1
 
0.2%
20 2
 
0.5%
19 2
 
0.5%
17 6
1.5%
16 2
 
0.5%
15 3
0.7%
14 2
 
0.5%
13 3
0.7%
12 6
1.5%

기타언어
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
0
405 
1
 
3
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 405
99.0%
1 3
 
0.7%
2 1
 
0.2%

Length

2024-05-18T07:53:17.999069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:53:18.429859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 405
99.0%
1 3
 
0.7%
2 1
 
0.2%

합계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct184
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean292.6577
Minimum0
Maximum3957
Zeros162
Zeros (%)39.6%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-18T07:53:19.078438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median13
Q3222
95-th percentile1925
Maximum3957
Range3957
Interquartile range (IQR)222

Descriptive statistics

Standard deviation634.18671
Coefficient of variation (CV)2.1669914
Kurtosis7.0888217
Mean292.6577
Median Absolute Deviation (MAD)13
Skewness2.7140653
Sum119697
Variance402192.79
MonotonicityNot monotonic
2024-05-18T07:53:19.662939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 162
39.6%
1 9
 
2.2%
3 8
 
2.0%
2 6
 
1.5%
4 6
 
1.5%
94 4
 
1.0%
8 3
 
0.7%
32 3
 
0.7%
81 3
 
0.7%
33 3
 
0.7%
Other values (174) 202
49.4%
ValueCountFrequency (%)
0 162
39.6%
1 9
 
2.2%
2 6
 
1.5%
3 8
 
2.0%
4 6
 
1.5%
5 3
 
0.7%
6 1
 
0.2%
7 3
 
0.7%
8 3
 
0.7%
10 1
 
0.2%
ValueCountFrequency (%)
3957 1
0.2%
3382 1
0.2%
2731 1
0.2%
2694 1
0.2%
2537 1
0.2%
2402 1
0.2%
2317 1
0.2%
2287 2
0.5%
2259 1
0.2%
2253 1
0.2%

Interactions

2024-05-18T07:52:56.432681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:45.548730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:50.613018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:55.038578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:59.389146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:04.734236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:09.705010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:13.856399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:19.540938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:23.738059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:28.573695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:33.147818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:37.974918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:42.794965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:47.693609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:56.899824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:45.847431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:50.876329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:55.293842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:59.763711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:05.072726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:10.012035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:14.108554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:19.790312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:24.003913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:28.836209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:33.465132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:38.325089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:43.083953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:47.971378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:57.288317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:46.129238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:51.115785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:55.667385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:00.124945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:05.395668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:10.273741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:14.407542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:20.030180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:24.260961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:29.099316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:33.790408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:38.621387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:43.405412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:48.302544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:57.815483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:46.419561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:51.371459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:55.936849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:00.400939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:05.732136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:10.547684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:14.754452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:20.282806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:24.536153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:29.361988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:34.105754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:38.913433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:43.757977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:48.604088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:58.243209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:46.820087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:51.832603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:56.222725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:00.742614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:06.087952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:10.846808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:15.184034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:20.567472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:24.791826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:29.686212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:34.470725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:39.252905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:44.022255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:48.986291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:58.534020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:47.139187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:52.074762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:56.444119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:01.080623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:06.400458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:11.104713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:15.722526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:20.848511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:25.045675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:29.994325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:34.775952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:39.498977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:44.324328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:49.327621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:58.901574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:47.495441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:52.347599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:56.740017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:01.470501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:06.774303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:11.386320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:16.110527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:21.128676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:25.314811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:30.324152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:35.062156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:39.913775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:44.707601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:49.880660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:59.199120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:47.811488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:52.766912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:57.031035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:01.874621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:07.169743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:11.655867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:16.420826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:21.416351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:25.598302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:30.671480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:35.442751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:40.271626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:45.100878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:51.532418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:59.536843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:48.067061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:53.128133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:57.282686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:02.138601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:07.499322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:11.999819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:16.828966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:21.676096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:25.941211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:30.954719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:35.746739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:40.560512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:45.356607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:52.438098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:59.963760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:48.332695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:53.422051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:57.546334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:02.483835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:07.858221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:12.272634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:17.281824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:21.959593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:26.265349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:31.247476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:36.091770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:40.877348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:45.683596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:53.615552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:53:00.317349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:48.642022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:53.684150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:57.770339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:02.931671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:08.091511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:12.507455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:17.667700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:22.276735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:26.575858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:31.506118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:36.392830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:41.224895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:45.936521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:54.284381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:53:00.611383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:48.939123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:53.972302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:58.058321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:03.359377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:08.368143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:12.714808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:18.146812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:22.613487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:27.191216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:31.830256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:36.673959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:41.492136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:46.232400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:54.675149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:53:00.892509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:49.240382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:54.258548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:58.474186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:03.711976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:08.662785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:13.060887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:18.567894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:22.943934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:27.508783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:32.164042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:36.971052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:41.750139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:46.772475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:55.057348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:53:01.312144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:49.808737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:54.528479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:58.786218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:04.094113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:09.138914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:13.320043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:18.913584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:23.219313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:27.886194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:32.521817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:37.339706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:42.066533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:47.123234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:55.537267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:53:01.631191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:50.168816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:54.761468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:51:59.084317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:04.436347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:09.379993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:13.578088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:19.240656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:23.460076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:28.204094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:32.788664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:37.603409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:42.363220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:47.399723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:52:56.000637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T07:53:19.992672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월기관/유형한국어영어일본어중국어베트남어타갈로그어몽골어프랑스어러시아어우즈벡어태국어네팔어인도네시아어아랍어스페인어기타언어합계
년월1.0000.2170.3030.1900.1490.2500.1340.2670.2640.0730.3960.2790.2110.0320.2710.3100.2450.1750.291
기관/유형0.2171.0000.4020.5750.6130.5970.6870.6750.5600.0000.5560.5310.5460.1020.6170.5580.5090.0000.724
한국어0.3030.4021.0000.6740.8230.7430.6140.7940.4970.0000.7780.8360.5460.0000.6520.4610.6410.1970.784
영어0.1900.5750.6741.0000.7740.7760.6880.7210.8090.0000.7070.7820.6960.0000.7190.6100.5950.5370.840
일본어0.1490.6130.8230.7741.0000.9430.7050.7790.6850.0000.7870.7830.8160.0000.7140.5730.6040.0000.855
중국어0.2500.5970.7430.7760.9431.0000.7360.7670.6660.0000.7540.7950.8640.0000.7430.5530.6420.1910.861
베트남어0.1340.6870.6140.6880.7050.7361.0000.7140.6830.0000.7390.7910.6530.6890.8670.7070.5860.9370.874
타갈로그어0.2670.6750.7940.7210.7790.7670.7141.0000.7020.0000.8600.8270.6390.2600.7320.7170.7470.3100.772
몽골어0.2640.5600.4970.8090.6850.6660.6830.7021.0000.0000.6570.7730.6680.4640.6990.4910.5240.2010.780
프랑스어0.0730.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
러시아어0.3960.5560.7780.7070.7870.7540.7390.8600.6570.0001.0000.8990.6790.0000.7770.6710.7460.0310.849
우즈벡어0.2790.5310.8360.7820.7830.7950.7910.8270.7730.0000.8991.0000.8180.0000.8180.6310.7800.0000.851
태국어0.2110.5460.5460.6960.8160.8640.6530.6390.6680.0000.6790.8181.0000.0000.8130.5770.5870.0000.815
네팔어0.0320.1020.0000.0000.0000.0000.6890.2600.4640.0000.0000.0000.0001.0000.0000.0000.3420.4550.270
인도네시아어0.2710.6170.6520.7190.7140.7430.8670.7320.6990.0000.7770.8180.8130.0001.0000.7080.6480.1870.922
아랍어0.3100.5580.4610.6100.5730.5530.7070.7170.4910.0000.6710.6310.5770.0000.7081.0000.5470.2780.675
스페인어0.2450.5090.6410.5950.6040.6420.5860.7470.5240.0000.7460.7800.5870.3420.6480.5471.0000.4740.642
기타언어0.1750.0000.1970.5370.0000.1910.9370.3100.2010.0000.0310.0000.0000.4550.1870.2780.4741.0000.422
합계0.2910.7240.7840.8400.8550.8610.8740.7720.7800.0000.8490.8510.8150.2700.9220.6750.6420.4221.000
2024-05-18T07:53:20.607049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
프랑스어기타언어네팔어기관/유형
프랑스어1.0000.0000.0000.000
기타언어0.0001.0000.7040.000
네팔어0.0000.7041.0000.101
기관/유형0.0000.0000.1011.000
2024-05-18T07:53:21.018312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월한국어영어일본어중국어베트남어타갈로그어몽골어러시아어우즈벡어태국어인도네시아어아랍어스페인어합계기관/유형프랑스어네팔어기타언어
년월1.000-0.155-0.228-0.160-0.127-0.251-0.111-0.314-0.123-0.300-0.362-0.379-0.414-0.236-0.2570.1030.0580.0310.101
한국어-0.1551.0000.8890.8530.8750.6550.8250.7010.8440.7040.4900.5530.4690.6370.8540.2450.0000.0000.150
영어-0.2280.8891.0000.8390.8150.6710.7600.7270.7940.7140.5700.6150.5180.6960.9110.3270.0000.0000.400
일본어-0.1600.8530.8391.0000.8980.8070.8690.7470.8880.8020.6110.5860.5430.6730.8540.3600.0000.0000.000
중국어-0.1270.8750.8150.8981.0000.7830.8980.7540.9420.8020.5710.5550.5410.6280.8200.3680.0000.0000.129
베트남어-0.2510.6550.6710.8070.7831.0000.7890.8100.8010.8970.7950.6490.6540.6330.7630.2820.0000.6930.701
타갈로그어-0.1110.8250.7600.8690.8980.7891.0000.7130.9100.7820.5790.5300.5420.6210.8310.3870.0000.1970.194
몽골어-0.3140.7010.7270.7470.7540.8100.7131.0000.7710.8300.6900.6450.6000.6110.7350.3150.0000.3460.128
러시아어-0.1230.8440.7940.8880.9420.8010.9100.7711.0000.8160.5730.5440.5650.6070.8030.2910.0000.0000.016
우즈벡어-0.3000.7040.7140.8020.8020.8970.7820.8300.8161.0000.7230.6890.6690.6180.7530.2740.0000.0000.000
태국어-0.3620.4900.5700.6110.5710.7950.5790.6900.5730.7231.0000.6630.7150.6890.7230.3260.0000.0000.000
인도네시아어-0.3790.5530.6150.5860.5550.6490.5300.6450.5440.6890.6631.0000.5510.5870.6190.2390.0000.0000.052
아랍어-0.4140.4690.5180.5430.5410.6540.5420.6000.5650.6690.7150.5511.0000.5490.6270.3150.0000.0000.119
스페인어-0.2360.6370.6960.6730.6280.6330.6210.6110.6070.6180.6890.5870.5491.0000.7950.2600.0000.2600.321
합계-0.2570.8540.9110.8540.8200.7630.8310.7350.8030.7530.7230.6190.6270.7951.0000.3090.0000.2670.204
기관/유형0.1030.2450.3270.3600.3680.2820.3870.3150.2910.2740.3260.2390.3150.2600.3091.0000.0000.1010.000
프랑스어0.0580.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.000
네팔어0.0310.0000.0000.0000.0000.6930.1970.3460.0000.0000.0000.0000.0000.2600.2670.1010.0001.0000.704
기타언어0.1010.1500.4000.0000.1290.7010.1940.1280.0160.0000.0000.0520.1190.3210.2040.0000.0000.7041.000

Missing values

2024-05-18T07:53:02.147170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T07:53:02.914612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

년월기관/유형한국어영어일본어중국어베트남어타갈로그어몽골어프랑스어러시아어우즈벡어태국어네팔어인도네시아어파키스탄어(우르두어)아랍어스페인어기타언어합계
0202404SNS000000000000000000
1202404게시판000000000000000000
2202404문자000000000000000000
3202404방문830848142001300000000150
4202404이동상담000000000000000000
5202404이메일000000000000000000
6202404전화321071412811152007000000000514
7202404화상상담000000000000000000
8202403SNS000000000000000000
9202403게시판000000000000000000
년월기관/유형한국어영어일본어중국어베트남어타갈로그어몽골어프랑스어러시아어우즈벡어태국어네팔어인도네시아어파키스탄어(우르두어)아랍어스페인어기타언어합계
399201908이메일127200000010030290063
400201908전화9328953155242147970326166214020031701840
401201908홈페이지010000000000000001
402201908화상상담000000000000000000
403201907방문16118436428100270572730701220504
404201907이동상담000000000000000000
405201907이메일275100000000000103091
406201907전화613476613323425811205602231640240291002221
407201907홈페이지020000000000000002
408201907화상상담000000000000000000