#res=DbService.getTrainData("F20000",3)#sqlalchemy查询结果--》rowproxy #res=DbService.getTestMysqlDb("F20000",3)#MySQLdb查询结果--》tuple #res=MetaDataDao.findByDrgId2("F20000")#PymysqlPool封装查询结果---》dict #row2Dataframe(res) #convert2Dataframe(res) #dict2Dataframe(res)#tuple转dataframe====>mysqlDb查询结果def convert2Dataframe(data):    df=pd.DataFrame(list(data),columns=["akc190","yka055","yp_sum","ypzf_yp","hl_sum"])    ss=df[["yka055","akc190"]]#dataframe数据选取    print(df)#dict转dataframedef dict2Dataframe(data):    df=pd.DataFrame(data)    df2=pd.DataFrame.from_dict(data)    print(df)#rowproxy转dataframedef row2Dataframe(data):    arrs=[]    for d in data:        flag1=type(d)        # todo 转tuple        res=d._row        arrs.append(res)    #todo list[tuple] 转dataframe    convert2Dataframe(arrs)#第二种：rowproxy转dataframedef row2Dataframe(data):    df=pd.DataFrame(data,columns=["akc190","yka055","yp_sum","ypzf_yp","hl_sum"])    ss=df[["yka055","akc190"]]#dataframe数据选取

pandas的df与spark的df进行互转

import pandas as pdfrom pyspark import SQLContextfrom pyspark.sql import SparkSessionimport pyspark.sql.types as typ'''pandas dataframe转spark df'''##直接调用官方api进行转换def createSpark():    spark=SparkSession.builder.getOrCreate()    df=pd.read_excel('C:\\Users\\shea\\Desktop\\测试.xlsx')    print(df)    #使用sqlContext转换    sqlContext=SQLContext(spark.sparkContext)    spark_df=sqlContext.createDataFrame(df)    spark_df.select("bah").show()#使用shema转换--针对某些列 有特殊值，不能模板匹配类型def convert2Spakr():    columns=[        ('bah',typ.StringType()),        ('name', typ.StringType()),        ('sex', typ.IntegerType()),        ('akc194', typ.StringType()),        ('zzfs', typ.StringType())    ]    schema=typ.StructType([        typ.StructField(index[0],index[1],False) for index in columns    ])    spark = SparkSession.builder.getOrCreate()    df = pd.read_excel('C:\\Users\\shea\\Desktop\\测试.xlsx')    df['akc194']=df['akc194'].map(lambda x:str(x))#操作某一列，将timestamp转为为string    #dataframe转list    ss=df.values.tolist()    ss_tuple=list(map(lambda x:tuple(x),ss))    spark_df=spark.createDataFrame(ss_tuple,schema=schema)    spark_df.show()if __name__ == '__main__':    #createSpark()    convert2Spakr()