pypetb.Capability
Module Contents
Classes
Capability analysis works as a model. |
- class pypetb.Capability.Capability(mydf, mydict)
Capability analysis works as a model. Once input parameter are specified, model is solved and available
to print different reports depending on the user requirement
Args:
- mydfpandas dataframe
At least the measures in a column. For LT analysis, batch column too.
- mydictdictionary
Value –> String. Measures column name | Batch –> Optional String. Batch ID column name | LSL –> Optional float. Lower specification
limit | HSL –> Optional float. Higher specification limit | Goal –> Optional float. Goal. ONE OF LSL OR HSL MUST BE SPECIFIED
Methods:
- getLog: string
printable string containing all individual calculations
- Normality_test: matplotlib figure
report to check sample normality
- Report: matplotlib figure
Capability report
Raises:
TypeError
- Init_01
mydict keys ar not correctly defined
- Init_02
Specified measures column name is not found
- Init_03
Dataframe contains null values
- Init_04
Specified measures column a non numerical type column
- getLog()
Return a string which contain all important calculations.
Returns:
- log: String
all step logged
- Normality_test()
Normality_test report is a figure that contain different chart and data description which helps to conclude if the measurement could be explained as a normal distribution so capability analysis could be done, or, inthe other hand, this analysis could not be take place. First, an histogram is showed, then, the probability plot. Third one is a time series plot and a descriptive data box. Finally, an advisement is showed based on p value.
Returns:
- Fig_NTmatplotlib figure
Set of charts