我想讀取類型爲map<string, int>
的cassandra列族中的數據並希望將其轉換爲Pandas數據框。我進一步想用Python在Python中訓練模型,如虹膜種類分類中提到的here。如何將Cassandra地圖轉換爲Pandas Dataframe
如果我會用csv來訓練模型。然後,它會是這個樣子的:
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
卡桑德拉列族:
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
代碼:
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)
我已經試過這種方法。但是'只打印輸出中的映射鍵(f1,f2,f3,f4)「僅打印df'。當我打印'df.values'時,它給出了[OrderedMapSerializedKey([(u'f1',11),(u'f2',1),(u'f3',6),(u'f4', 1),(u'f5',2)])]'。我無法使用這些值來訓練它。它應該返回數字值和第一行中的標題。就像我在csv中提到的一樣 – Naresh