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Taux d'accidents du Travail (AT taux)

(5ce8c14d06e3e715bfd57eba) [more]

Taux de fréquence et taux de gravité des accidents de travail par EPIC et du Groupe SNCF. Ce jeu de données est actualisé tous les mois.

Data summary

File '30e45890-5e73-4b7c-80c3-ad4328fd216a'
- Table ‘30e45890-5e73-4b7c-80c3-ad4328fd216a’ consists of 82 data rows along seven dimensions: ‘rhumba’, ‘nombre_accidents’, ‘nombre_de_jours_d_absences’, ‘tf_mensuel’, ‘tf_annuel_glissant_12_mois’, ‘tg_mensuel’ and ‘tg_annuel_glissant_12_mois’

Size: 4.9 KB Source: data.europa.eu Last updated: 2022-01-13 18:58

Four line items stand out against weak regression fit between ‘tf_annuel_glissant_12_mois’ and ‘tg_mensuel’

tf_annuel_glissant_12_mois tg_mensuel Point cloud Regression Anomaly Deviation Non-linear 1 Dec 2019 Top insights
‘tf_mensuel’ with a deviation from the trend in 1 Apr 2020

rhumba tf_mensuel Aggregation Sum Time series Anomaly Decreasing trend Deviation Trend 1 Apr 2020 Top insights
17 line items stand out against moderate regression fit between ‘tf_annuel_glissant_12_mois’ and ‘tg_annuel_glissant_12_mois’

tf_annuel_glissant_12_mois tg_annuel_glissant_12_mois Point cloud Regression Anomaly Correlation Deviation Linear Relation 1 Dec 2020 Top insights
One statistical outlier identified in distribution of values in column ‘tf_mensuel’

tf_mensuel Histogram Anomaly Outlier 1 Apr 2020 Data quality assessment Top insights
22 statistical outliers identified in distribution of values in column ‘tf_annuel_glissant_12_mois’

tf_annuel_glissant_12_mois Histogram Anomaly Outlier 1 Nov 2020 Data quality assessment Top insights
One statistical outlier identified in distribution of values in column ‘nombre_accidents’

nombre_accidents Histogram Anomaly Outlier 1 Apr 2020 Data quality assessment Top insights
‘tg_annuel_glissant_12_mois’ by ‘rhumba’ with an overall increase but now leveling off with one deviation

rhumba tg_annuel_glissant_12_mois Aggregation Sum Time series Anomaly Deviation Increasing trend Trend 1 Jan 2015
One line item stands out against very good regression fit between ‘tf_mensuel’ and ‘tg_mensuel’

tf_mensuel tg_mensuel Point cloud Regression Anomaly Constant Deviation Linear Very good fit 1 Dec 2019
One line item stands out against cluster between ‘tf_mensuel’ and ‘tg_annuel_glissant_12_mois’

tf_mensuel tg_annuel_glissant_12_mois Point cloud Anomaly Cluster Deviation Relation 1 Apr 2020
19 line items stand out against weak regression fit between ‘tf_annuel_glissant_12_mois’ and ‘tf_mensuel’

tf_annuel_glissant_12_mois tf_mensuel Point cloud Regression Anomaly Deviation Non-linear 1 Nov 2020
Five line items stand out against cluster between ‘tg_annuel_glissant_12_mois’ and ‘tg_mensuel’

tg_annuel_glissant_12_mois tg_mensuel Point cloud Anomaly Cluster Deviation Relation 1 Dec 2019
‘tf_annuel_glissant_12_mois’ by ‘rhumba’ remaining steady since 1 Apr 2020

rhumba tf_annuel_glissant_12_mois Aggregation Sum Time series Anomaly Deviation Trend Trend change Very good fit

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Dimension	Priority
For table 30e45890-5e73-4b7c-80c3-ad4328fd216a* in lines 1–83 of input file 30e45890-5e73-4b7c-80c3-ad4328fd216a…*
rhumba Date/Time	0.8333333333333333
nombre_accidents Integer Number	0.3333333333333333
nombre_de_jours_d_absences Integer Number	0.3333333333333333
tf_mensuel Floating-Point Number	0.6666666666666666
tf_annuel_glissant_12_mois Floating-Point Number	0.6666666666666666
tg_mensuel Floating-Point Number	0.8333333333333333
tg_annuel_glissant_12_mois Floating-Point Number	0.8333333333333333

Dimension	Annotations
For table 30e45890-5e73-4b7c-80c3-ad4328fd216a* in lines 1–83 of input file 30e45890-5e73-4b7c-80c3-ad4328fd216a…*
rhumba Date/Time
nombre_accidents Integer Number
nombre_de_jours_d_absences Integer Number
tf_mensuel Floating-Point Number
tf_annuel_glissant_12_mois Floating-Point Number
tg_mensuel Floating-Point Number
tg_annuel_glissant_12_mois Floating-Point Number

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Taux d'accidents du Travail (AT taux)

Data summary

File '30e45890-5e73-4b7c-80c3-ad4328fd216a'

Four line items stand out against weak regression fit between ‘tf_annuel_glissant_12_mois’ and ‘tg_mensuel’

‘tf_mensuel’ with a deviation from the trend in 1 Apr 2020

17 line items stand out against moderate regression fit between ‘tf_annuel_glissant_12_mois’ and ‘tg_annuel_glissant_12_mois’

One statistical outlier identified in distribution of values in column ‘tf_mensuel’

22 statistical outliers identified in distribution of values in column ‘tf_annuel_glissant_12_mois’

One statistical outlier identified in distribution of values in column ‘nombre_accidents’

‘tg_annuel_glissant_12_mois’ by ‘rhumba’ with an overall increase but now leveling off with one deviation

One line item stands out against very good regression fit between ‘tf_mensuel’ and ‘tg_mensuel’

One line item stands out against cluster between ‘tf_mensuel’ and ‘tg_annuel_glissant_12_mois’

19 line items stand out against weak regression fit between ‘tf_annuel_glissant_12_mois’ and ‘tf_mensuel’

Five line items stand out against cluster between ‘tg_annuel_glissant_12_mois’ and ‘tg_mensuel’

‘tf_annuel_glissant_12_mois’ by ‘rhumba’ remaining steady since 1 Apr 2020