feature.get_stats()

Rasgo makes it easy for you to get the stats for any feature stored within Rasgo from Python without needing to use the GUI. Once you have a feature, you can get its stats by calling get_stats.

feature = rasgo.get.feature(id)

fstats = feature.get_stats()

You can access the individual stats either directly as

fstats.meanVal

Or create a dictionary and work with the stats in the dictionary

fstats_dict = fstats.dict() fstats_dict['meanVal']

The available statistics are:

Field Name	Statistic
recCt	Record Count
distinctCt	Number of Distinct Values
nullRecCt	Number Null
zeroValRecCt	Number that is zero value
meanVal	Mean
medianVal	Median
maxVal	Maximum
minVal	Minimum
sumVal	Sum
stdDevVal	Standard Deviation
varianceVal	Variance
rangeVal	Range
skewVal	Skewness
kurtosisVal	Kurtosis
q1Val	25th Percentile
q3Val	75th Percentile
IQRVal	IQR
pct5Val	5th Percentile
pct95Val	95th Percentile
outlierCt	Total number of outliers
lowOutlier	Value below which a record is an outlier
highOutlier	Value above which a record is an outlier

If you have recently uploaded a dataframe with publish.features_from_df, you can easily get these statistics for each column in a pandas dataframe. publish.features_from_df Returns a featureset

featureset = rasgo.publish.features_from_df(df, dimensions, features, granularity, tags)

You can get a list of features contained in this featureset using get.features_by_featureset. features = rasgo.get.features_by_featureset(featureset.id)

And you can create the stats dataframe for this list of features (or any other list you’ve created) by

fstatlist = [] for f in featurelist: statdict = f.get_stats().dict() statdict['featureName'] = f.name fstatlist.append(statdict) df = pd.DataFrame(fstatlist)