python之如何将 Cassandra Map 转换为 Pandas Dataframe

我想从 map<string, int> 类型的 cassandra 列族中读取数据并想将其转换为 Pandas 数据框。我还想用它来训练 python 中提到的模型 here在鸢尾花种类的分类中。

如果，我会使用 csv 来训练模型。那么它看起来像这样:

label,  f1, f2, f3, f4, f5 
  0  ,  11 , 1, 6 , 1,  2   
  1  ,  5,   5, 1 , 2,  6 
  0  ,  12,  9, 3 , 6,  8 
  0  ,  9,  3,  8,  1,  0  

Cassandra 列族:

                  FeatureSet                    |   label 
 
{'f1': 11, 'f2': 1, 'f3': 6, 'f4': 1, 'f5': 2}  |     0 
{'f1': 5, 'f2':  5, 'f3': 1, 'f4': 2, 'f5': 6}  |     1 
{'f1': 12, 'f2': 9, 'f3': 3, 'f4': 6, 'f5': 8}  |     0 
{'f1': 9, 'f2': 3, 'f3': 8, 'f4': 1, 'f5': 0}   |     0 

代码:

import pandas as pd 
from sklearn2pmml import PMMLPipeline 
from sklearn.tree import DecisionTreeClassifier 
from cassandra.cluster import Cluster 
 
CASSANDRA_HOST = ['172.16.X.Y','172.16.X1.Y1']  
CASSANDRA_PORT = 9042 
CASSANDRA_DB = "KEYSPACE" 
CASSANDRA_TABLE = "COLUMNFAMILY" 
 
cluster = Cluster(contact_points=CASSANDRA_HOST, port=CASSANDRA_PORT) 
session = cluster.connect(CASSANDRA_DB) 
 
sql_query = "SELECT * FROM {}.{};".format(CASSANDRA_DB, CASSANDRA_TABLE) 
 
df = pd.DataFrame() 
 
for row in session.execute(sql_query):   
            What should i write here and get X_train, Y_train in pandas dataframe  
 
 
 
iris_pipeline = PMMLPipeline([ 
    ("classifier", DecisionTreeClassifier()) 
]) 
iris_pipeline.fit(X_train, Y_train) 

请您参考如下方法:

您可以使用 this approach :

import pandas as pd 
from cassandra.cluster import Cluster 
 
def pandas_factory(colnames, rows): 
    return pd.DataFrame(rows, columns=colnames) 
 
CASSANDRA_HOST = ['172.16.X.Y','172.16.X1.Y1']  
CASSANDRA_PORT = 9042 
CASSANDRA_DB = "KEYSPACE" 
CASSANDRA_TABLE = "COLUMNFAMILY" 
 
cluster = Cluster(contact_points=CASSANDRA_HOST, port=CASSANDRA_PORT) 
session = cluster.connect(CASSANDRA_DB) 
 
session.row_factory = pandas_factory 
session.default_fetch_size = None 
 
query = "SELECT * FROM {}.{};".format(CASSANDRA_DB, CASSANDRA_TABLE) 
 
rslt = session.execute(query, timeout=None) 
df = rslt._current_rows