我用python api导入数据到DolphinDB分布式表，分布式表按月+按股票分区，建库和导入代码如下：

import os
import glob
import pandas as pd
import datetime as dt
import dolphindb as ddb

if __name__ == "__main__":
    s = ddb.session()
    s.connect(host="10.63.16.165", port=8921, userid="admin", password="123456")
    if not s.existsDatabase("dfs://minute_price"):
        s.run("valuep = database(, VALUE, date(1990.01M + (0..600)))")
        s.run("""tickerp = database(, HASH, [SYMBOL, 20])""")
        s.run("""price_data = database("dfs://minute_price", COMPO, [valuep, tickerp])""")
        columns = """`code`wind_code`name`date`time`open`high`low`close`volume`turnover`match_items`interest`datetime"""
        types = """[SYMBOL,SYMBOL,SYMBOL,DATE,INT,DOUBLE,DOUBLE,DOUBLE,DOUBLE,DOUBLE,DOUBLE,DOUBLE,DOUBLE,TIMESTAMP]"""
        s.run("""table_new = price_data.createPartitionedTable(table(10:0, {cols}, {types}), `price_data,
                  `datetime`code)""".format(cols=columns, types=types))
        print("NEW TABLE CREATED....")
    # else:
    #     s.dropDatabase("dfs://minute_price")


    DIR = "/mnt/paicdom/Packages/Wind/"
    target = "Minute"
    start_date = "2015-04-01"
    dates = pd.date_range(start_date, "2015-05-01", freq="M")
    for date in dates.tolist():
        date_str = date.strftime("%Y%m")
        dir = DIR + date_str + "/" + date_str + "_" + target
        folder_list = os.listdir(dir)
        for mk in folder_list:
            sub_path = os.path.join(dir, mk)
            print("Starting to work on dir: {d}".format(d=sub_path))
            sub_dir_list = os.listdir(sub_path)
            for sub_dir in sub_dir_list:
                sub_sub_dir = os.path.join(sub_path, sub_dir)
                file_list = os.listdir(sub_sub_dir)
                for file_name in file_list:
                    file_name = os.path.join(sub_sub_dir, file_name)
                    data = pd.read_csv(file_name)
                    time = data.time.astype("str")
                    cond_sel = ~time.str.startswith("1").copy()
                    time[cond_sel] = "0" + time[cond_sel]
                    data["datetime"] = data.date.astype("str") + time.str[0:4]
                    data["datetime"] = pd.to_datetime(data["datetime"], format="%Y%m%d%H%M")
                    data["date"] = pd.to_datetime(data["date"], format="%Y%m%d")
                    data = data.rename(columns={"turover":"turnover", "volumw":"volume"})
                    data["code"] = data["code"].astype("str")
                    data["name"] = data["name"].astype("str")
                    # print(data)
                    s.upload({"tmp_data": data})
                    query = """select code,wind_code,name,date(date) as date,time,open,high,low,
                                close,volume,turnover,match_items,interest,timestamp(datetime) as datetime from tmp_data"""
                    s.run("tableInsert(loadTable('{db}', `{tb}), ({sel}))".format(db="dfs://minute_price",
                                                                                  tb="price_data",
                                                                                  sel=query))
                    print("inserted %s" % file_name)

我导入了2015年4月一个月数据，程序写完了，可是查询只能看到2015.04.01的数据，如下图所示，

请教各位大佬这是为什么？