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a un point décimal a est l'identifiant de la variable (attention à ne pas utiliser le mots réservés comme identifiant), = est l'opérateur d'affectation
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Pour obtenir plus de décimales que la précision standard de Python, il faut utiliser le module decimal qui permet de travailler avec une précision arbitraire
[PDF] Rounding Methods in Different Software - ISD Scotland
2 jui 2019 · Python also uses a “round half to even” method Analysts in ISD often have to round numbers to a smaller number of decimal places
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Le module decimal permet d'effectuer des calculs exacts sur les nombres décimaux, dans les limites d'une précision fixée par l'utilisateur (mais par défaut
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de Python comme support à l'apprentissage de la programmation en lycée général et On peut contourner le problème à l'aide de la bibliothèque decimal
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comparativement à d'autres langages, le Python est assez proche d'un Le module decimal « est basé sur un modèle en virgule flottante conçu pour les
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Python stores 53 bits for the mantissa of each floating point number, so this series is truncated The truncated series, converted back to decimal is:
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To be able to use the Python math library A numeric literal without a decimal point produces an intvalue us around the limitations of ints?
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19200_6Rounding_Methods_in_Different_Software_v1_0.pdf Public Health &
Intelligence
Rounding Methods in Different Software
Document Control
Version Version 1.0
Date Issued June 2019
Author Statistical Governance Team
Comments to NSS.isdGPD@nhs.net
Version Date Comment Author
Version 0.1 May 2019 1st version of paper (ISD version) GPD Team Version 0.2 Jun 2019 2nd version of paper (ISD version) GPD Team Version 1.0 Jun 2019 Published version on ISD website GPD Team 2 R rounds numbers slightly differently to the traditional method used in SPSS. Rounding is an important and widely used method of disclosure control and it is important that there is a clearƵŶĚĞƌƐƚĂŶĚŝŶŐŽĨ͛ƐƌŽƵŶĚŝŶŐŵĞƚŚŽĚ͘
SPSS rounds numbers using the traditional ŵĞƚŚŽĚŽĨ͞ƌŽƵŶĚŝŶŐŚĂůĨĂǁĂLJĨƌŽŵnjĞƌŽ͕͟ǁŚĞƌĞǀĂůƵĞƐ
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rounding. For example, 1.5 and 2.5 would both be rounded to 2 when using R. While this is less common than the method used in SPSS, this is still a valid rounding technique and is accepted amongst the mathematical community. The idea behind this method is that it eliminates bias away from zero, as numbers are evenly split for rounding up or down, rather than .5 always being roundedup. LJƚŚŽŶĂůƐŽƵƐĞƐĂ͞ƌŽƵŶĚŚĂůĨƚŽĞǀĞŶ͟ŵĞƚŚŽĚ͘
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round(1.5, 0) ## [1] 2 round(2.5, 0) ## [1] 2 round(3.5, 0) ## [1] 4 Analysts in ISD often have to round numbers to a smaller number of decimal places. For example, if you had a percentage of people seen within 4 hours in Emergency Departments at 90.25%, this would be rounded down to 90.2% using R, when this would normally be expected to round up to90.3%. As a result, the output would be slightly lower than what would be expected.
round(90.25, 1) ## [1] 90.2The R package ͞janitor͟ ĐŽŶƚĂŝŶƐĂƌŽƵŶĚͺŚĂůĨͺƵƉ;ͿĨƵŶĐƚŝŽŶǁŚŝĐŚƌĞƉůŝĐĂƚĞƐƚŚĞ͞ƌŽƵŶĚŚĂůĨĂǁĂLJ
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library(janitor) round_half_up(1.5, 0) ## [1] 2 round_half_up(2.5, 0) ## [1] 3 3 round_half_up(90.25, 1) ## [1] 90.3 As you can see, the round_half_up function works in the traditional method that most of us are used to. It is strongly advised that the round_half_up function should be used in all analysis.