Overview

Dataset statistics

Number of variables19
Number of observations598334
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory285.8 MiB
Average record size in memory500.8 B

Variable types

Text1
Categorical8
Boolean2
Numeric6
DateTime2

Dataset

DescriptionEMT - Estimaciones del tiempo de llegada del Bus
URLhttps://apidocs.emtmadrid.es/#api-Block_3_TRANSPORT_BUSEMTMAD-arrives

Variable descriptions

PKIdentificador único (Primary Key) del dataset, compuesto por <datetime>_B<bus>_L<linea>_S<parada>
dateFecha de la petición a la API
datetimeFecha y hora de la petición a la API
lineLínea de bus
stopParada de bus
busNúmero identificador del bus
positionBusLonLongitud de las coordenadas del bus
positionBusLatLatitud de las coordenadas del bus
DistanceBusDistancia del bus a la parada (en metros)
destinationDestino del itinerario
deviationDesviación en el cálculo del ETA
StartTimeHora de inicio de la línea
StopTimeHora de fin de la línea
MinimunFrequencyFrecuencia mínima de la línea
MaximumFrequencyFrecuencia máxima de la línea
isHeadVariable booleana para indicar si la parada es la cabecera de la línea
dayType Tipo de día (LA: laboral, FE: festivo, SA: sábado)
strikeVariable para indicar si ese día hay huelga (S) o no (N)
estimateArriveTiempo estimado de espera del bus (en segundos)

Alerts

date has constant value ""Constant
dayType has constant value ""Constant
strike has constant value ""Constant
stop has a high cardinality: 283 distinct valuesHigh cardinality
bus has a high cardinality: 182 distinct valuesHigh cardinality
isHead is highly imbalanced (57.9%)Imbalance
deviation is highly imbalanced (> 99.9%)Imbalance
estimateArrive is highly skewed (γ1 = 43.1852418)Skewed
positionBusLon is highly skewed (γ1 = 65.67607433)Skewed
positionBusLat is highly skewed (γ1 = -85.712563)Skewed
estimateArrive has 14093 (2.4%) zerosZeros
DistanceBus has 25283 (4.2%) zerosZeros

Reproduction

Analysis started2024-03-21 12:11:10.937978
Analysis finished2024-03-21 12:11:46.789568
Duration35.85 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

PK
Text

Identificador único (Primary Key) del dataset, compuesto por _B_L_S

Distinct598236
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size61.1 MiB
2024-03-21T13:11:47.463941image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length44
Median length43
Mean length42.133484
Min length39

Characters and Unicode

Total characters25209896
Distinct characters18
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique598138 ?
Unique (%)> 99.9%

Sample

1st row2024-03-13 08:00:01.765317_B513_L27_S56
2nd row2024-03-13 08:00:01.765317_B521_L27_S56
3rd row2024-03-13 08:00:01.810182_B513_L27_S60
4th row2024-03-13 08:00:01.810182_B521_L27_S60
5th row2024-03-13 08:00:01.810759_B513_L27_S66
ValueCountFrequency (%)
2024-03-13 598334
50.0%
22:57:52.951111_b2260_l129_s132 2
 
< 0.1%
22:56:55.394377_b2260_l129_s3247 2
 
< 0.1%
22:56:55.370013_b2260_l129_s3245 2
 
< 0.1%
22:59:02.506093_b2260_l129_s30 2
 
< 0.1%
22:57:55.429266_b2260_l129_s3594 2
 
< 0.1%
22:56:57.823445_b2260_l129_s5606 2
 
< 0.1%
22:55:56.740337_b2263_l135_s5604 2
 
< 0.1%
22:57:53.065915_b2260_l129_s509 2
 
< 0.1%
22:57:53.020156_b2260_l129_s203 2
 
< 0.1%
Other values (598227) 598316
50.0%
2024-03-21T13:11:49.160500image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2806263
11.1%
0 2611227
10.4%
1 2472669
9.8%
3 2444352
9.7%
4 1976647
 
7.8%
_ 1795002
 
7.1%
5 1698959
 
6.7%
7 1277971
 
5.1%
- 1196668
 
4.7%
: 1196668
 
4.7%
Other values (8) 5733470
22.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18029888
71.5%
Connector Punctuation 1795002
 
7.1%
Other Punctuation 1795002
 
7.1%
Uppercase Letter 1795002
 
7.1%
Dash Punctuation 1196668
 
4.7%
Space Separator 598334
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2806263
15.6%
0 2611227
14.5%
1 2472669
13.7%
3 2444352
13.6%
4 1976647
11.0%
5 1698959
9.4%
7 1277971
7.1%
6 1011995
 
5.6%
8 897893
 
5.0%
9 831912
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 598334
33.3%
L 598334
33.3%
S 598334
33.3%
Other Punctuation
ValueCountFrequency (%)
: 1196668
66.7%
. 598334
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 1795002
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1196668
100.0%
Space Separator
ValueCountFrequency (%)
598334
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23414894
92.9%
Latin 1795002
 
7.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2806263
12.0%
0 2611227
11.2%
1 2472669
10.6%
3 2444352
10.4%
4 1976647
8.4%
_ 1795002
7.7%
5 1698959
7.3%
7 1277971
 
5.5%
- 1196668
 
5.1%
: 1196668
 
5.1%
Other values (5) 3938468
16.8%
Latin
ValueCountFrequency (%)
B 598334
33.3%
L 598334
33.3%
S 598334
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25209896
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2806263
11.1%
0 2611227
10.4%
1 2472669
9.8%
3 2444352
9.7%
4 1976647
 
7.8%
_ 1795002
 
7.1%
5 1698959
 
6.7%
7 1277971
 
5.1%
- 1196668
 
4.7%
: 1196668
 
4.7%
Other values (8) 5733470
22.7%

line
Categorical

Línea de bus

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.1 MiB
49
61761 
174
54823 
134
54672 
70
49559 
27
47468 
Other values (10)
330051 

Length

Max length3
Median length3
Mean length2.5945174
Min length2

Characters and Unicode

Total characters1552388
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27
2nd row27
3rd row27
4th row27
5th row27

Common Values

ValueCountFrequency (%)
49 61761
10.3%
174 54823
9.2%
134 54672
9.1%
70 49559
 
8.3%
27 47468
 
7.9%
67 46139
 
7.7%
129 41073
 
6.9%
107 41060
 
6.9%
176 37704
 
6.3%
42 37687
 
6.3%
Other values (5) 126388
21.1%

Length

2024-03-21T13:11:49.535926image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
49 61761
10.3%
174 54823
9.2%
134 54672
9.1%
70 49559
 
8.3%
27 47468
 
7.9%
67 46139
 
7.7%
129 41073
 
6.9%
107 41060
 
6.9%
176 37704
 
6.3%
42 37687
 
6.3%
Other values (5) 126388
21.1%

Most occurring characters

ValueCountFrequency (%)
7 413590
26.6%
1 355720
22.9%
4 208943
13.5%
2 126228
 
8.1%
9 102834
 
6.6%
3 92128
 
5.9%
0 90619
 
5.8%
6 83843
 
5.4%
5 44315
 
2.9%
8 34168
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1552388
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 413590
26.6%
1 355720
22.9%
4 208943
13.5%
2 126228
 
8.1%
9 102834
 
6.6%
3 92128
 
5.9%
0 90619
 
5.8%
6 83843
 
5.4%
5 44315
 
2.9%
8 34168
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1552388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 413590
26.6%
1 355720
22.9%
4 208943
13.5%
2 126228
 
8.1%
9 102834
 
6.6%
3 92128
 
5.9%
0 90619
 
5.8%
6 83843
 
5.4%
5 44315
 
2.9%
8 34168
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1552388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 413590
26.6%
1 355720
22.9%
4 208943
13.5%
2 126228
 
8.1%
9 102834
 
6.6%
3 92128
 
5.9%
0 90619
 
5.8%
6 83843
 
5.4%
5 44315
 
2.9%
8 34168
 
2.2%

stop
Categorical

HIGH CARDINALITY 

Parada de bus

Distinct283
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.7 MiB
1487
 
13539
3252
 
8568
2653
 
8511
1488
 
8503
207
 
5168
Other values (278)
554045 

Length

Max length5
Median length4
Mean length3.7011285
Min length2

Characters and Unicode

Total characters2214511
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row56
2nd row56
3rd row60
4th row60
5th row66

Common Values

ValueCountFrequency (%)
1487 13539
 
2.3%
3252 8568
 
1.4%
2653 8511
 
1.4%
1488 8503
 
1.4%
207 5168
 
0.9%
205 5157
 
0.9%
203 5133
 
0.9%
3253 5126
 
0.9%
30 5116
 
0.9%
3826 5109
 
0.9%
Other values (273) 528404
88.3%

Length

2024-03-21T13:11:49.853476image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1487 13539
 
2.3%
3252 8568
 
1.4%
2653 8511
 
1.4%
1488 8503
 
1.4%
207 5168
 
0.9%
205 5157
 
0.9%
203 5133
 
0.9%
3253 5126
 
0.9%
30 5116
 
0.9%
3826 5109
 
0.9%
Other values (273) 528404
88.3%

Most occurring characters

ValueCountFrequency (%)
1 304273
13.7%
5 299509
13.5%
3 282354
12.8%
2 276931
12.5%
6 217248
9.8%
4 205171
9.3%
0 177870
8.0%
8 174111
7.9%
7 159119
7.2%
9 117925
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2214511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 304273
13.7%
5 299509
13.5%
3 282354
12.8%
2 276931
12.5%
6 217248
9.8%
4 205171
9.3%
0 177870
8.0%
8 174111
7.9%
7 159119
7.2%
9 117925
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2214511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 304273
13.7%
5 299509
13.5%
3 282354
12.8%
2 276931
12.5%
6 217248
9.8%
4 205171
9.3%
0 177870
8.0%
8 174111
7.9%
7 159119
7.2%
9 117925
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2214511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 304273
13.7%
5 299509
13.5%
3 282354
12.8%
2 276931
12.5%
6 217248
9.8%
4 205171
9.3%
0 177870
8.0%
8 174111
7.9%
7 159119
7.2%
9 117925
 
5.3%

isHead
Boolean

IMBALANCE 

Variable booleana para indicar si la parada es la cabecera de la línea

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.1 MiB
False
547182 
True
 
51152
ValueCountFrequency (%)
False 547182
91.5%
True 51152
 
8.5%
2024-03-21T13:11:50.106600image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

destination
Categorical

Destino del itinerario

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.2 MiB
MONTECARMELO
85436 
BARRIO PEÑAGRANDE
80413 
PLAZA CASTILLA
76392 
PITIS
58329 
VALDEBEBAS
51427 
Other values (9)
246337 

Length

Max length22
Median length14
Mean length11.883378
Min length5

Characters and Unicode

Total characters7110229
Distinct characters24
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPLAZA CASTILLA
2nd rowPLAZA CASTILLA
3rd rowPLAZA CASTILLA
4th rowPLAZA CASTILLA
5th rowPLAZA CASTILLA

Common Values

ValueCountFrequency (%)
MONTECARMELO 85436
14.3%
BARRIO PEÑAGRANDE 80413
13.4%
PLAZA CASTILLA 76392
12.8%
PITIS 58329
9.7%
VALDEBEBAS 51427
8.6%
ALSACIA 47869
8.0%
MANOTERAS 39371
6.6%
HORTALEZA 39351
6.6%
LAS TABLAS SUR 34275
5.7%
LAS TABLAS NORTE 27396
 
4.6%
Other values (4) 58075
9.7%

Length

2024-03-21T13:11:50.450608image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
montecarmelo 85436
 
8.9%
peñagrande 80413
 
8.4%
barrio 80413
 
8.4%
plaza 76392
 
8.0%
castilla 76392
 
8.0%
las 61671
 
6.4%
tablas 61671
 
6.4%
pitis 58329
 
6.1%
valdebebas 51427
 
5.4%
alsacia 47869
 
5.0%
Other values (13) 278641
29.1%

Most occurring characters

ValueCountFrequency (%)
A 1383333
19.5%
L 600343
 
8.4%
E 588620
 
8.3%
R 547372
 
7.7%
S 489080
 
6.9%
O 405069
 
5.7%
T 399817
 
5.6%
I 377712
 
5.3%
360320
 
5.1%
N 311225
 
4.4%
Other values (14) 1647338
23.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6749909
94.9%
Space Separator 360320
 
5.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1383333
20.5%
L 600343
8.9%
E 588620
8.7%
R 547372
 
8.1%
S 489080
 
7.2%
O 405069
 
6.0%
T 399817
 
5.9%
I 377712
 
5.6%
N 311225
 
4.6%
B 246633
 
3.7%
Other values (13) 1400705
20.8%
Space Separator
ValueCountFrequency (%)
360320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6749909
94.9%
Common 360320
 
5.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1383333
20.5%
L 600343
8.9%
E 588620
8.7%
R 547372
 
8.1%
S 489080
 
7.2%
O 405069
 
6.0%
T 399817
 
5.9%
I 377712
 
5.6%
N 311225
 
4.6%
B 246633
 
3.7%
Other values (13) 1400705
20.8%
Common
ValueCountFrequency (%)
360320
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7029816
98.9%
None 80413
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 1383333
19.7%
L 600343
 
8.5%
E 588620
 
8.4%
R 547372
 
7.8%
S 489080
 
7.0%
O 405069
 
5.8%
T 399817
 
5.7%
I 377712
 
5.4%
360320
 
5.1%
N 311225
 
4.4%
Other values (13) 1566925
22.3%
None
ValueCountFrequency (%)
Ñ 80413
100.0%

deviation
Categorical

IMBALANCE 

Desviación en el cálculo del ETA

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.7 MiB
0
598332 
288
 
2

Length

Max length3
Median length1
Mean length1.0000067
Min length1

Characters and Unicode

Total characters598338
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 598332
> 99.9%
288 2
 
< 0.1%

Length

2024-03-21T13:11:50.812410image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-21T13:11:51.096051image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
0 598332
> 99.9%
288 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 598332
> 99.9%
8 4
 
< 0.1%
2 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 598338
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 598332
> 99.9%
8 4
 
< 0.1%
2 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 598338
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 598332
> 99.9%
8 4
 
< 0.1%
2 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 598338
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 598332
> 99.9%
8 4
 
< 0.1%
2 2
 
< 0.1%

bus
Categorical

HIGH CARDINALITY 

Número identificador del bus

Distinct182
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.7 MiB
2137
 
10005
2134
 
8849
2133
 
8592
2132
 
8310
2135
 
8212
Other values (177)
554366 

Length

Max length4
Median length4
Mean length3.8378381
Min length3

Characters and Unicode

Total characters2296309
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row513
2nd row521
3rd row513
4th row521
5th row513

Common Values

ValueCountFrequency (%)
2137 10005
 
1.7%
2134 8849
 
1.5%
2133 8592
 
1.4%
2132 8310
 
1.4%
2135 8212
 
1.4%
2260 8102
 
1.4%
9125 7883
 
1.3%
2471 7737
 
1.3%
2464 7703
 
1.3%
9120 7613
 
1.3%
Other values (172) 515328
86.1%

Length

2024-03-21T13:11:51.340540image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2137 10005
 
1.7%
2134 8849
 
1.5%
2133 8592
 
1.4%
2132 8310
 
1.4%
2135 8212
 
1.4%
2260 8102
 
1.4%
9125 7883
 
1.3%
2471 7737
 
1.3%
2464 7703
 
1.3%
9120 7613
 
1.3%
Other values (172) 515328
86.1%

Most occurring characters

ValueCountFrequency (%)
5 428304
18.7%
2 423674
18.5%
4 263698
11.5%
1 213202
9.3%
3 192432
8.4%
7 184268
8.0%
6 170101
 
7.4%
0 166468
 
7.2%
8 155274
 
6.8%
9 98888
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2296309
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 428304
18.7%
2 423674
18.5%
4 263698
11.5%
1 213202
9.3%
3 192432
8.4%
7 184268
8.0%
6 170101
 
7.4%
0 166468
 
7.2%
8 155274
 
6.8%
9 98888
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2296309
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 428304
18.7%
2 423674
18.5%
4 263698
11.5%
1 213202
9.3%
3 192432
8.4%
7 184268
8.0%
6 170101
 
7.4%
0 166468
 
7.2%
8 155274
 
6.8%
9 98888
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2296309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 428304
18.7%
2 423674
18.5%
4 263698
11.5%
1 213202
9.3%
3 192432
8.4%
7 184268
8.0%
6 170101
 
7.4%
0 166468
 
7.2%
8 155274
 
6.8%
9 98888
 
4.3%

estimateArrive
Real number (ℝ)

SKEWED  ZEROS 

Tiempo estimado de espera del bus (en segundos)

Distinct2588
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1129.2919
Minimum0
Maximum999999
Zeros14093
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size9.1 MiB
2024-03-21T13:11:51.602067image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile50
Q1255
median530
Q3870
95-th percentile1365
Maximum999999
Range999999
Interquartile range (IQR)615

Descriptive statistics

Standard deviation23109.991
Coefficient of variation (CV)20.464143
Kurtosis1863.5844
Mean1129.2919
Median Absolute Deviation (MAD)300
Skewness43.185242
Sum6.7569374 × 108
Variance5.3407169 × 108
MonotonicityNot monotonic
2024-03-21T13:11:51.921727image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14093
 
2.4%
112 877
 
0.1%
172 848
 
0.1%
232 837
 
0.1%
233 829
 
0.1%
412 825
 
0.1%
173 823
 
0.1%
180 820
 
0.1%
352 820
 
0.1%
413 794
 
0.1%
Other values (2578) 576768
96.4%
ValueCountFrequency (%)
0 14093
2.4%
1 343
 
0.1%
2 312
 
0.1%
3 316
 
0.1%
4 263
 
< 0.1%
5 272
 
< 0.1%
6 293
 
< 0.1%
7 257
 
< 0.1%
8 303
 
0.1%
9 262
 
< 0.1%
ValueCountFrequency (%)
999999 320
0.1%
2700 2
 
< 0.1%
2699 1
 
< 0.1%
2698 2
 
< 0.1%
2697 1
 
< 0.1%
2695 1
 
< 0.1%
2693 3
 
< 0.1%
2691 2
 
< 0.1%
2690 1
 
< 0.1%
2689 2
 
< 0.1%

DistanceBus
Real number (ℝ)

ZEROS 

Distancia del bus a la parada (en metros)

Distinct11811
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2458.6632
Minimum-1485
Maximum27157
Zeros25283
Zeros (%)4.2%
Negative2313
Negative (%)0.4%
Memory size9.1 MiB
2024-03-21T13:11:52.354583image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-1485
5-th percentile24
Q1887
median1939
Q33564
95-th percentile6450
Maximum27157
Range28642
Interquartile range (IQR)2677

Descriptive statistics

Standard deviation2058.1719
Coefficient of variation (CV)0.83711013
Kurtosis2.1536088
Mean2458.6632
Median Absolute Deviation (MAD)1238
Skewness1.2766121
Sum1.4711018 × 109
Variance4236071.5
MonotonicityNot monotonic
2024-03-21T13:11:52.779921image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25283
 
4.2%
-1 918
 
0.2%
830 197
 
< 0.1%
733 196
 
< 0.1%
696 195
 
< 0.1%
600 194
 
< 0.1%
697 193
 
< 0.1%
1061 192
 
< 0.1%
569 191
 
< 0.1%
646 191
 
< 0.1%
Other values (11801) 570584
95.4%
ValueCountFrequency (%)
-1485 1
< 0.1%
-969 1
< 0.1%
-672 1
< 0.1%
-529 1
< 0.1%
-486 1
< 0.1%
-483 1
< 0.1%
-346 1
< 0.1%
-341 1
< 0.1%
-317 1
< 0.1%
-314 1
< 0.1%
ValueCountFrequency (%)
27157 1
< 0.1%
20810 1
< 0.1%
19758 1
< 0.1%
18385 1
< 0.1%
18239 1
< 0.1%
18198 1
< 0.1%
18072 1
< 0.1%
18030 1
< 0.1%
17975 1
< 0.1%
17965 1
< 0.1%

datetime
Date

Fecha y hora de la petición a la API

Distinct240350
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Memory size9.1 MiB
Minimum2024-03-13 08:00:01.765317
Maximum2024-03-13 22:59:36.378432
2024-03-21T13:11:53.230211image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-21T13:11:53.700525image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

date
Date

CONSTANT 

Fecha de la petición a la API

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.1 MiB
Minimum2024-03-13 00:00:00
Maximum2024-03-13 00:00:00
2024-03-21T13:11:54.044234image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-21T13:11:54.369132image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

positionBusLon
Real number (ℝ)

SKEWED 

Longitud de las coordenadas del bus

Distinct44977
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.6859704
Minimum-3.7341244
Maximum0
Zeros81
Zeros (%)< 0.1%
Negative598253
Negative (%)> 99.9%
Memory size9.1 MiB
2024-03-21T13:11:54.735524image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-3.7341244
5-th percentile-3.7136074
Q1-3.6959401
median-3.6885849
Q3-3.6799993
95-th percentile-3.6484984
Maximum0
Range3.7341244
Interquartile range (IQR)0.015940745

Descriptive statistics

Standard deviation0.046925738
Coefficient of variation (CV)-0.012730905
Kurtosis5150.7228
Mean-3.6859704
Median Absolute Deviation (MAD)0.0078188502
Skewness65.676074
Sum-2205441.4
Variance0.0022020249
MonotonicityNot monotonic
2024-03-21T13:11:55.154427image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.682079884 2412
 
0.4%
-3.688422131 1456
 
0.2%
-3.693550381 1067
 
0.2%
-3.664880434 1067
 
0.2%
-3.688710463 1061
 
0.2%
-3.705829598 893
 
0.1%
-3.692177664 712
 
0.1%
-3.688586292 637
 
0.1%
-3.688495343 572
 
0.1%
-3.725200986 569
 
0.1%
Other values (44967) 587888
98.3%
ValueCountFrequency (%)
-3.734124388 1
< 0.1%
-3.734116208 1
< 0.1%
-3.734110755 2
< 0.1%
-3.734105302 1
< 0.1%
-3.734102575 2
< 0.1%
-3.734099849 1
< 0.1%
-3.734091499 2
< 0.1%
-3.734078036 2
< 0.1%
-3.73407531 2
< 0.1%
-3.73406713 2
< 0.1%
ValueCountFrequency (%)
0 81
< 0.1%
-3.578007767 14
 
< 0.1%
-3.608182303 1
 
< 0.1%
-3.60821038 1
 
< 0.1%
-3.608210624 1
 
< 0.1%
-3.608222343 1
 
< 0.1%
-3.608248468 1
 
< 0.1%
-3.608271664 1
 
< 0.1%
-3.608481448 2
 
< 0.1%
-3.608498301 1
 
< 0.1%

positionBusLat
Real number (ℝ)

SKEWED 

Latitud de las coordenadas del bus

Distinct44977
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.466236
Minimum0
Maximum40.673134
Zeros81
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size9.1 MiB
2024-03-21T13:11:55.450768image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile40.428719
Q140.467263
median40.47133
Q340.482079
95-th percentile40.499322
Maximum40.673134
Range40.673134
Interquartile range (IQR)0.014815961

Descriptive statistics

Standard deviation0.47125847
Coefficient of variation (CV)0.01164572
Kurtosis7357.0535
Mean40.466236
Median Absolute Deviation (MAD)0.0057603363
Skewness-85.712563
Sum24212325
Variance0.22208455
MonotonicityNot monotonic
2024-03-21T13:11:55.911575image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40.48036006 2412
 
0.4%
40.46825881 1456
 
0.2%
40.48778618 1067
 
0.2%
40.50548572 1067
 
0.2%
40.4665018 1061
 
0.2%
40.46415416 893
 
0.1%
40.51048521 712
 
0.1%
40.46763543 637
 
0.1%
40.46798163 572
 
0.1%
40.49518427 569
 
0.1%
Other values (44967) 587888
98.3%
ValueCountFrequency (%)
0 81
< 0.1%
40.4040894 2
 
< 0.1%
40.40408989 17
 
< 0.1%
40.40409038 3
 
< 0.1%
40.40409087 4
 
< 0.1%
40.40409136 13
 
< 0.1%
40.40409283 5
 
< 0.1%
40.40409332 5
 
< 0.1%
40.4040943 25
 
< 0.1%
40.40409479 13
 
< 0.1%
ValueCountFrequency (%)
40.67313425 24
 
< 0.1%
40.65915359 23
 
< 0.1%
40.59692139 270
< 0.1%
40.59691793 18
 
< 0.1%
40.51655589 6
 
< 0.1%
40.51654381 2
 
< 0.1%
40.51654093 2
 
< 0.1%
40.51653792 1
 
< 0.1%
40.51651572 9
 
< 0.1%
40.51651082 1
 
< 0.1%

dayType
Categorical

CONSTANT 

Tipo de día (LA: laboral, FE: festivo, SA: sábado)

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.2 MiB
LA
598334 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1196668
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
LA 598334
100.0%

Length

2024-03-21T13:11:56.283391image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-21T13:11:56.492606image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
la 598334
100.0%

Most occurring characters

ValueCountFrequency (%)
L 598334
50.0%
A 598334
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1196668
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 598334
50.0%
A 598334
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1196668
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 598334
50.0%
A 598334
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1196668
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
L 598334
50.0%
A 598334
50.0%

StartTime
Categorical

Hora de inicio de la línea

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.9 MiB
06:00
306319 
06:10
61761 
06:25
54672 
05:30
49559 
05:55
47468 
Other values (3)
78555 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2991670
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05:55
2nd row05:55
3rd row05:55
4th row05:55
5th row05:55

Common Values

ValueCountFrequency (%)
06:00 306319
51.2%
06:10 61761
 
10.3%
06:25 54672
 
9.1%
05:30 49559
 
8.3%
05:55 47468
 
7.9%
06:15 41060
 
6.9%
06:20 23972
 
4.0%
06:30 13523
 
2.3%

Length

2024-03-21T13:11:56.712457image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-21T13:11:56.945177image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
06:00 306319
51.2%
06:10 61761
 
10.3%
06:25 54672
 
9.1%
05:30 49559
 
8.3%
05:55 47468
 
7.9%
06:15 41060
 
6.9%
06:20 23972
 
4.0%
06:30 13523
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 1359787
45.5%
: 598334
20.0%
6 501307
 
16.8%
5 287695
 
9.6%
1 102821
 
3.4%
2 78644
 
2.6%
3 63082
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2393336
80.0%
Other Punctuation 598334
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1359787
56.8%
6 501307
 
20.9%
5 287695
 
12.0%
1 102821
 
4.3%
2 78644
 
3.3%
3 63082
 
2.6%
Other Punctuation
ValueCountFrequency (%)
: 598334
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2991670
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1359787
45.5%
: 598334
20.0%
6 501307
 
16.8%
5 287695
 
9.6%
1 102821
 
3.4%
2 78644
 
2.6%
3 63082
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2991670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1359787
45.5%
: 598334
20.0%
6 501307
 
16.8%
5 287695
 
9.6%
1 102821
 
3.4%
2 78644
 
2.6%
3 63082
 
2.1%

StopTime
Categorical

Hora de fin de la línea

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.9 MiB
23:45
526894 
23:30
71440 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2991670
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row23:30
2nd row23:30
3rd row23:30
4th row23:30
5th row23:30

Common Values

ValueCountFrequency (%)
23:45 526894
88.1%
23:30 71440
 
11.9%

Length

2024-03-21T13:11:57.460181image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-21T13:11:57.687290image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
23:45 526894
88.1%
23:30 71440
 
11.9%

Most occurring characters

ValueCountFrequency (%)
3 669774
22.4%
2 598334
20.0%
: 598334
20.0%
4 526894
17.6%
5 526894
17.6%
0 71440
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2393336
80.0%
Other Punctuation 598334
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 669774
28.0%
2 598334
25.0%
4 526894
22.0%
5 526894
22.0%
0 71440
 
3.0%
Other Punctuation
ValueCountFrequency (%)
: 598334
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2991670
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 669774
22.4%
2 598334
20.0%
: 598334
20.0%
4 526894
17.6%
5 526894
17.6%
0 71440
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2991670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 669774
22.4%
2 598334
20.0%
: 598334
20.0%
4 526894
17.6%
5 526894
17.6%
0 71440
 
2.4%

MinimunFrequency
Real number (ℝ)

Frecuencia mínima de la línea

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1873485
Minimum3
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 MiB
2024-03-21T13:11:57.950659image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q14
median7
Q39
95-th percentile12
Maximum12
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.6407197
Coefficient of variation (CV)0.36741223
Kurtosis-0.98041952
Mean7.1873485
Median Absolute Deviation (MAD)2
Skewness0.059017423
Sum4300435
Variance6.9734008
MonotonicityNot monotonic
2024-03-21T13:11:58.222336image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
9 169098
28.3%
7 116443
19.5%
4 111320
18.6%
6 71872
12.0%
3 47468
 
7.9%
12 41073
 
6.9%
11 41060
 
6.9%
ValueCountFrequency (%)
3 47468
 
7.9%
4 111320
18.6%
6 71872
12.0%
7 116443
19.5%
9 169098
28.3%
11 41060
 
6.9%
12 41073
 
6.9%
ValueCountFrequency (%)
12 41073
 
6.9%
11 41060
 
6.9%
9 169098
28.3%
7 116443
19.5%
6 71872
12.0%
4 111320
18.6%
3 47468
 
7.9%

MaximumFrequency
Real number (ℝ)

Frecuencia máxima de la línea

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.387937
Minimum12
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 MiB
2024-03-21T13:11:58.491118image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile12
Q117
median22
Q324
95-th percentile30
Maximum30
Range18
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.813608
Coefficient of variation (CV)0.22506182
Kurtosis-0.45107401
Mean21.387937
Median Absolute Deviation (MAD)2
Skewness-0.25468157
Sum12797130
Variance23.170822
MonotonicityNot monotonic
2024-03-21T13:11:58.814633image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
22 160843
26.9%
24 102732
17.2%
15 61761
 
10.3%
26 54672
 
9.1%
17 49559
 
8.3%
12 47468
 
7.9%
30 46139
 
7.7%
20 37704
 
6.3%
21 23933
 
4.0%
29 13523
 
2.3%
ValueCountFrequency (%)
12 47468
 
7.9%
15 61761
 
10.3%
17 49559
 
8.3%
20 37704
 
6.3%
21 23933
 
4.0%
22 160843
26.9%
24 102732
17.2%
26 54672
 
9.1%
29 13523
 
2.3%
30 46139
 
7.7%
ValueCountFrequency (%)
30 46139
 
7.7%
29 13523
 
2.3%
26 54672
 
9.1%
24 102732
17.2%
22 160843
26.9%
21 23933
 
4.0%
20 37704
 
6.3%
17 49559
 
8.3%
15 61761
 
10.3%
12 47468
 
7.9%

strike
Boolean

CONSTANT 

Variable para indicar si ese día hay huelga (S) o no (N)

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.1 MiB
False
598334 
ValueCountFrequency (%)
False 598334
100.0%
2024-03-21T13:11:59.054812image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Missing values

2024-03-21T13:11:43.004169image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-21T13:11:44.474499image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

PKlinestopisHeaddestinationdeviationbusestimateArriveDistanceBusdatetimedatepositionBusLonpositionBusLatdayTypeStartTimeStopTimeMinimunFrequencyMaximumFrequencystrike
02024-03-13 08:00:01.765317_B513_L27_S562756FalsePLAZA CASTILLA051347318412024-03-13 08:00:01.7653172024-03-13-3.69054240.423739LA05:5523:303.012.0N
12024-03-13 08:00:01.765317_B521_L27_S562756FalsePLAZA CASTILLA052131312212024-03-13 08:00:01.7653172024-03-13-3.68901940.429011LA05:5523:303.012.0N
122024-03-13 08:00:01.810182_B513_L27_S602760FalsePLAZA CASTILLA051328211592024-03-13 08:00:01.8101822024-03-13-3.69054240.423739LA05:5523:303.012.0N
132024-03-13 08:00:01.810182_B521_L27_S602760FalsePLAZA CASTILLA05211166462024-03-13 08:00:01.8101822024-03-13-3.68901940.429011LA05:5523:303.012.0N
222024-03-13 08:00:01.810759_B513_L27_S662766FalsePLAZA CASTILLA05131233912024-03-13 08:00:01.8107592024-03-13-3.69054240.423739LA05:5523:303.012.0N
232024-03-13 08:00:01.810759_B526_L27_S662766FalsePLAZA CASTILLA052642413782024-03-13 08:00:01.8107592024-03-13-3.69345140.415523LA05:5523:303.012.0N
322024-03-13 08:00:01.811512_B521_L27_S522752FalsePLAZA CASTILLA052141917752024-03-13 08:00:01.8115122024-03-13-3.68901940.429011LA05:5523:303.012.0N
332024-03-13 08:00:01.811512_B537_L27_S522752FalsePLAZA CASTILLA05371176562024-03-13 08:00:01.8115122024-03-13-3.69011940.438093LA05:5523:303.012.0N
512024-03-13 08:00:01.812652_B511_L27_S852785FalsePLAZA CASTILLA05111845912024-03-13 08:00:01.8126522024-03-13-3.70230640.405239LA05:5523:303.012.0N
522024-03-13 08:00:01.812652_B524_L27_S852785FalsePLAZA CASTILLA05242954892024-03-13 08:00:01.8126522024-03-13-3.70209640.405283LA05:5523:303.012.0N
PKlinestopisHeaddestinationdeviationbusestimateArriveDistanceBusdatetimedatepositionBusLonpositionBusLatdayTypeStartTimeStopTimeMinimunFrequencyMaximumFrequencystrike
11344462024-03-13 22:59:07.675931_B2545_L173_S59271735927FalseSANCHINARRO02545511962024-03-13 22:59:07.6759312024-03-13-3.65747540.493921LA06:0023:457.021.0N
11344472024-03-13 22:59:07.708629_B8851_L176_S59841765984FalseLAS TABLAS SUR0885143220012024-03-13 22:59:07.7086292024-03-13-3.66830440.493645LA06:0023:456.020.0N
11344482024-03-13 22:59:07.708629_B8864_L176_S59841765984FalseLAS TABLAS SUR08864126367092024-03-13 22:59:07.7086292024-03-13-3.68839040.470399LA06:0023:456.020.0N
11344512024-03-13 22:59:07.744969_B4965_L42_S5996425996TruePLAZA CASTILLA0496511002024-03-13 22:59:07.7449692024-03-13-3.72881440.473979LA06:0023:457.024.0N
11344522024-03-13 22:59:07.744969_B5550_L42_S5996425996TruePLAZA CASTILLA05550155159082024-03-13 22:59:07.7449692024-03-13-3.68905040.467641LA06:0023:457.024.0N
11344532024-03-13 22:59:07.748610_B2067_L174_S5102217451022TruePLAZA CASTILLA0206765137072024-03-13 22:59:07.7486102024-03-13-3.62195440.482080LA06:0023:457.022.0N
11344562024-03-13 22:59:07.770061_B2067_L174_S5102317451023FalseVALDEBEBAS0206740933522024-03-13 22:59:07.7700612024-03-13-3.62195440.482080LA06:0023:457.022.0N
11344572024-03-13 22:59:07.770061_B2141_L174_S5102317451023FalseVALDEBEBAS02141122581142024-03-13 22:59:07.7700612024-03-13-3.66704840.489136LA06:0023:457.022.0N
11344602024-03-13 22:59:36.378432_B2290_L174_S32561743256FalseVALDEBEBAS022901960138472024-03-13 22:59:36.3784322024-03-13-3.62309240.482330LA06:0023:457.022.0N
11344612024-03-13 22:59:36.378432_B8879_L174_S32561743256FalseVALDEBEBAS0887974648912024-03-13 22:59:36.3784322024-03-13-3.67613740.469620LA06:0023:457.022.0N