pyspark.sql.functions.replace() 函数用于替换字符串中的特定子字符串。它的语法如下: replace(str, search, replace) 其中:str:要进行替换操作的字符串列或表达式。search:要搜索并替换的子字符串。replace:用于替换匹配项的新字符串。 这个函数将在给定的字符串列或表达式中查找所有匹配 search 的子字符串,并用...
代码运行次数:0 运行 AI代码解释 df=pd.DataFrame([['Sam',28,88],['Flora',28,90],['Run',1,60]],columns=['name','age','score'])print(">> 打印DataFrame:")print(df)print("\n")Spark_df=spark.createDataFrame(df)print(">> 打印SparkDataFrame:")Spark_df.show()#>>打印DataFrame:# n...
from lib.regression import LabeledPoint, LinearRegressionWithSGD, LinearRegressionModel # Load and parse the data def parsePoint(line): values = [float(x) for x in line.replace(',', ' ').split(' ')] return LabeledPoint(values[0], values[1:]) data = sc.textFile("data/mllib/ridge-...
跟cast()是同一个函数 cast(dataType) #转换数据类型 startswith(other) #判断列中每个值是否以指定字符开头,返回布尔值 endswith(“string”) #判断列中每个值是否以指定字符结尾,返回布尔值 isNotNull() #判断列中的值
代码运行次数:0 运行 AI代码解释 df.select(df.age.alias('age_value'),'name') 查询某列为null的行: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 from pyspark.sql.functionsimportisnull df=df.filter(isnull("col_a")) 输出list类型,list中每个元素是Row类: ...
In PySpark,fillna() from DataFrame class or fill() from DataFrameNaFunctions is used to replace NULL/None values on all or selected multiple columns with either zero(0), empty string, space, or any constant literal values. AdvertisementsWhile working on PySpark DataFrame we often need to ...
#Register the DataFrame as a SQL temporary viewdf.CreateOrReplaceTempView("people") sqlDF = spark.sql("SELECT * FROM people") sqlDF.show()#+---+---+#| age| name|#+---+---+#+null|Jackson|#| 30| Martin|#| 19| Melvin|#+---|---| 您需要从某个表中选择所有...
1|0fill关键字的用法 Replace null values, alias for na.fill(). DataFrame.fillna() and DataFrameNaFunctions.fill() are aliases of each other. Parameters value –int, long, float, string, bool or dict. Value to replace null values with. If the value is a dict, then subset is ignored ...
df.na.replace(['Alice', 'Bob'], ['A', 'B'], 'name').show()+---+---+---+| age|height|name|+---+---+---+| 10| 80| A|| 5| null| B||null| 10| Tom||null| null|null|+---+---+---+df.show()+---+---+---+| age|height| name|+---+---+---+| 10...
") return df print("int-->0,double-->mean,string-->unknow") df = df.na.replace('', 'unkown') # 将空字符串填充为unkown df = df.fillna('unkown', subset = string_tz) # 将string的NULL填充为unkown df = df.fillna(0, subset = int_tz) # 用均值填充连续类特征中的null值 # 计算...