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unit: def hasUniqueness()
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id: 140
unit: def withKLLProfiling()
file: pydeequ/profiles.py
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id: 141
unit: def setKLLParameters()
file: pydeequ/profiles.py
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id: 142
unit: def useRepository()
file: pydeequ/profiles.py
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id: 143
unit: def saveOrAppendResult()
file: pydeequ/profiles.py
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id: 144
unit: def __init__()
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id: 145
unit: def __init__()
file: pydeequ/scala_utils.py
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id: 146
unit: def _set_jvm()
file: pydeequ/analyzers.py
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id: 147
unit: def onData()
file: pydeequ/analyzers.py
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id: 148
unit: def useRepository()
file: pydeequ/analyzers.py
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id: 149
unit: def saveOrAppendResult()
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id: 150
unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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unit: def __init__()
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id: 164
unit: def __init__()
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id: 165
unit: def onData()
file: pydeequ/suggestions.py
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id: 166
unit: def _set_jvm()
file: pydeequ/suggestions.py
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number of parameters: 2

id: 167
unit: def _anomaly_jvm()
file: pydeequ/anomaly_detection.py
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size: 2 LOC
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number of parameters: 1

id: 168
unit: def __init__()
file: pydeequ/anomaly_detection.py
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id: 169
unit: def _anomaly_jvm()
file: pydeequ/anomaly_detection.py
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size: 2 LOC
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id: 170
unit: def __init__()
file: pydeequ/anomaly_detection.py
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id: 171
unit: def __init__()
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id: 172
unit: def __init__()
file: pydeequ/anomaly_detection.py
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id: 173
unit: def pysparkDF_to_pandasDF()
file: pydeequ/pandas_utils.py
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size: 2 LOC
McCabe index: 1
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id: 174
unit: def createColumnProfileRunner()
file: pydeequ/__init__.py
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id: 175
unit: def createAnalysisRunner()
file: pydeequ/__init__.py
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id: 176
unit: def createCheck()
file: pydeequ/__init__.py
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size: 2 LOC
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id: 177
unit: def addFilterableContstraint()
file: pydeequ/checks.py
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size: 2 LOC
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id: 178
unit: def _isNewestPointNonAnomalous()
file: pydeequ/checks.py
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size: 2 LOC
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id: 179
unit: def evaluate()
file: pydeequ/checks.py
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id: 180
unit: def requiredAnalyzers()
file: pydeequ/checks.py
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id: 181
unit: def __init__()
file: pydeequ/repository.py
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id: 182
unit: def current_milli_time()
file: pydeequ/repository.py
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id: 183
unit: def status()
file: pydeequ/verification.py
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id: 184
unit: def checkResults()
file: pydeequ/verification.py
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id: 185
unit: def metrics()
file: pydeequ/verification.py
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id: 186
unit: def successMetricsAsDataFrame()
file: pydeequ/verification.py
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id: 187
unit: def checkResultsAsDataFrame()
file: pydeequ/verification.py
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id: 188
unit: def run()
file: pydeequ/verification.py
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id: 189
unit: def __init__()
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id: 190
unit: def __str__()
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id: 191
unit: def lowValue()
file: pydeequ/metrics.py
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id: 192
unit: def highValue()
file: pydeequ/metrics.py
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id: 193
unit: def count()
file: pydeequ/metrics.py
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id: 194
unit: def __str__()
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id: 195
unit: def buckets()
file: pydeequ/metrics.py
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id: 196
unit: def parameters()
file: pydeequ/metrics.py
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id: 197
unit: def data()
file: pydeequ/metrics.py
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id: 198
unit: def computePercentiles()
file: pydeequ/metrics.py
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id: 199
unit: def apply()
file: pydeequ/metrics.py
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id: 200
unit: def argmax()
file: pydeequ/metrics.py
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id: 201
unit: def profiles()
file: pydeequ/profiles.py
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id: 202
unit: def column()
file: pydeequ/profiles.py
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id: 203
unit: def completeness()
file: pydeequ/profiles.py
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id: 204
unit: def approximateNumDistinctValues()
file: pydeequ/profiles.py
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id: 205
unit: def dataType()
file: pydeequ/profiles.py
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id: 206
unit: def isDataTypeInferred()
file: pydeequ/profiles.py
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id: 207
unit: def typeCounts()
file: pydeequ/profiles.py
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id: 208
unit: def histogram()
file: pydeequ/profiles.py
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id: 209
unit: def __str__()
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id: 210
unit: def __str__()
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id: 211
unit: def kll()
file: pydeequ/profiles.py
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id: 212
unit: def mean()
file: pydeequ/profiles.py
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number of parameters: 1

id: 213
unit: def maximum()
file: pydeequ/profiles.py
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number of parameters: 1

id: 214
unit: def minimum()
file: pydeequ/profiles.py
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number of parameters: 1

id: 215
unit: def sum()
file: pydeequ/profiles.py
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number of parameters: 1

id: 216
unit: def stdDev()
file: pydeequ/profiles.py
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number of parameters: 1

id: 217
unit: def approxPercentiles()
file: pydeequ/profiles.py
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number of parameters: 1

id: 218
unit: def apply()
file: pydeequ/scala_utils.py
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id: 219
unit: def apply()
file: pydeequ/scala_utils.py
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id: 220
unit: def to_scala_seq()
file: pydeequ/scala_utils.py
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id: 221
unit: def to_scala_map()
file: pydeequ/scala_utils.py
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id: 222
unit: def scala_map_to_dict()
file: pydeequ/scala_utils.py
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number of parameters: 2

id: 223
unit: def scala_map_to_java_map()
file: pydeequ/scala_utils.py
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id: 224
unit: def __init__()
file: pydeequ/analyzers.py
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id: 225
unit: def successMetricsAsDataFrame()
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id: 226
unit: def run()
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id: 227
unit: def _analyzer_jvm()
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id: 228
unit: def _analyzer_jvm()
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id: 229
unit: def _analyzer_jvm()
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id: 230
unit: def _analyzer_jvm()
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id: 231
unit: def _analyzer_jvm()
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id: 232
unit: def _analyzer_jvm()
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id: 233
unit: def _analyzer_jvm()
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id: 234
unit: def _analyzer_jvm()
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id: 235
unit: def _analyzer_jvm()
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id: 236
unit: def _analyzer_jvm()
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id: 237
unit: def _analyzer_jvm()
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id: 238
unit: def _analyzer_jvm()
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id: 239
unit: def __init__()
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id: 240
unit: def _analyzer_jvm()
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id: 241
unit: def _analyzer_jvm()
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id: 242
unit: def _analyzer_jvm()
file: pydeequ/analyzers.py
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number of parameters: 1

id: 243
unit: def __init__()
file: pydeequ/suggestions.py
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number of parameters: 2

id: 244
unit: def rule_jvm()
file: pydeequ/suggestions.py
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number of parameters: 1

id: 245
unit: def rule_jvm()
file: pydeequ/suggestions.py
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id: 246
unit: def __init__()
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id: 247
unit: def rule_jvm()
file: pydeequ/suggestions.py
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id: 248
unit: def rule_jvm()
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id: 249
unit: def rule_jvm()
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id: 250
unit: def rule_jvm()
file: pydeequ/suggestions.py
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id: 251
unit: def rule_jvm()
file: pydeequ/suggestions.py
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size: 2 LOC
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number of parameters: 1

id: 252
unit: def hasPattern()
file: pydeequ/checks.py
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number of parameters: 6

id: 253
unit: def useSparkSession()
file: pydeequ/profiles.py
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number of parameters: 2