Functions 78 9.7 Tuples 79 9.8 Named Tuples 79 9.9 Destructuring Assignment and Multiple Return Values 79 9.10 Property destructuring 83 9.11 Argument destructuring 83 9.12 Varargs Functions 84 84 9.13 Optional Arguments 86 9.14 Keyword Arguments 87 9.15 Evaluation Scope of Default Values 88 9.16 Do-Block Syntax for Function Arguments 88 9.17 Function composition and piping 90 9.18 20.12 Broadcasting ..... 288 20.13 Implementation ..... 289 21 Missing Values ..... 292 21.1 Propagation of Missing Values ..... 292 21.2 Equality and Comparison Operators ..... 293 21.3 Logical

1 Optional Integer NA Support Pandas has gained the ability to hold integer dtypes with missing values. This long requested feature is enabled through the use of extension types. Note: IntegerArray is will infer to integer dtype. The display of the Series will also use the NaN to indicate missing values in string outputs. (GH20700, GH20747, GH22441, GH21789, GH22346) ```python In [1]: s = pd.Series([1 may be changed at a future date. See Nullable Integer Data Type for more. ## 1.1.2 Accessing the values in a Series or Index Series.array and Index.array have been added for extracting the array backing

threshold definitions • you can define very flexible problem thresholds, called triggers, referencing values from the backend database ## Highly configurable alerting • sending notifications can be customized (5 minutes, an hour, a day) and then display an aggregated value for this period, instead of all values. The aggregation options are as follows: • min • max • avg • count • sum • first (first value configure ways of displaying operational data for current problems, i.e. the latest item values as opposed to the item values at the time of the problem. Operational data display can be configured in the filter

215 Math-LOG10E.....216 Math-PI.....216 Math- SQRT1_2 ..... 216 Math - SQRT2 ..... 217 Exponential Functions ..... 217 Pow() ..... 217 sqrt() ..... 218 cbrt() ..... 219 exp() ..... 219 clear() .....266 delete(key) .....267 entries() .....268 forEach .....268 keys() .....269 values() .....270 The for...of Loop .....270 Weak Maps .....271 Sets .....271 Set Properties .. 273 clear() .....274 delete() .....274 entries() .....275 forEach .....276 has() .....276 values() and keys() .....277 Weak Set .....279 Iterator .....279 28. ES6 – CLASSES .....282 Object-Oriented

SparseTensor(indices=Tensor("Placeholder_8:0", shape=(?, 2), dtype=int64), values=Tensor("Placeholder_7:0", shape=(?,), dtype=float32), dense_shape=T mean represent the mean of the random values to generate • stddev represent the standard deviation of the random values to generate • seed represent the values to generate random number ## RandomUniform t)) where, • minval represent the lower bound of the random values to generate • maxval represent the upper bound of the random values to generate ## TruncatedNormal Generates value using truncated

Experimental NA scalar to denote missing values A new pd.NA value (singleton) is introduced to represent scalar missing values. Up to now, pandas used several values to represent missing data: np.nan is used 1.3.3 Boolean data type with missing values support We’ve added BooleanDtype / BooleanArray, an extension type dedicated to boolean data that can hold missing values. The default bool data type based on bool-dtype NumPy array, the column can only hold True or False, and not missing values. This new BooleanArray can store missing values as well by keeping track of this in a separate mask. (GH29555, GH30095, GH31131)

default'.SRC(KEY INT, VALUE STRING) USING PARQUET; INSERT INTO TABLE spark_catalog.default'.SRC VALUES (11215016, 'Kent Yao');  --isolation=LEVEL set the transaction isolation level --nullemptystring=[true/false] zookeeper .connection.max.retry .wait|30000|Max amount of time to wait between retries for BOUNDED\_EXPONENTIAL_ BACKOFF policy can reach, or max time until elapsed for UNTIL\_ELAPSED policy to connect the zookeeper

default'.SRC(KEY INT, VALUE STRING) USING PARQUET; INSERT INTO TABLE spark_catalog.default'.SRC VALUES (11215016, 'Kent Yao');  --isolation=LEVEL set the transaction isolation level --nullemptystring=[true/false] zookeeper .connection.max.retry .wait|30000|Max amount of time to wait between retries for BOUNDED\_EXPONENTIAL_ BACKOFF policy can reach, or max time until elapsed for UNTIL\_ELAPSED policy to connect the zookeeper

indicator / dummy variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . 490 2.8.9 Factorizing values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 494 2.8.10 Examples missing data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 521 2.10.1 Values considered “missing” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 521 2.10 . . . . . . . . . . . 526 2.10.5 NA values in GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 2.10.6 Filling missing values: fillna . . . . . . . . . . . . . . .