编程错误：（psycopg2.ProgrammingError）无法适应类型“numpy.ndarray”

我正在使用 pandas 创建一个 python 脚本来读取具有多个行值的文件。

读取后，我需要构建这些值的数组，然后将其分配给数据帧行值。

我使用的代码是

import re
import numpy as np
import pandas as pd
master_data = pd.DataFrame()
temp_df = pd.DataFrame()
new_df = pd.DataFrame()

for f in data:


##Reading the file in pandas which is in excel format 
#
file_df = pd.read_excel(f)


filename = file_df['Unnamed: 1'][2]


##Skipping first 24 rows to get the required reading values
column_names = ['start_time','xxx_value']
data_df = pd.read_excel(f, names=column_names, skiprows=25)


array =np.array([])

   for i in data_df.iterrows():
       array = np.append(array,i[1][1])


   temp_df['xxx_value'] = [array]
   temp_df['Filename'] = filename
   temp_df['sub_id']=       
   temp_df['Filename'].str.split('_',1).str[1].str.strip() 
   temp_df['sen_site']=    
   temp_df['Filename'].str.split('_',1).str[0].str.strip()
   temp_df['sampling_interval'] = 15
   temp_df['start_time'] = data_df['start_time'][2]


   new_df= new_df.append(xxx_df)

   new_df.index = new_df.index + 1
   new_df=new_df.sort_index()
   new_df.index.name='record_id'

  new_df = new_df.drop("Filename",1)    ##dropping the Filename as it          
  is not needed to be loaded in postgresql

 ##Rearrange to postgresql format
 column_new_df = new_df.columns.tolist()
 column_new_df.
 insert(4,column_new_df.pop(column_new_df.index('xxx_value')))
 new_df = new_df.reindex(columns = column_new_df)

 print(new_df)

当我尝试将数组数据插入 Postgresql 时，此代码不起作用。

它给了我一个错误，指出：

编程错误：（psycopg2.ProgrammingError）无法调整类型 'numpy.ndarray'

在我看来，最有效的方法是让 psycopg2 始终了解 np.ndarray(s)。可以通过注册一个适配器来做到这一点：

import numpy as np
from psycopg2.extensions import register_adapter, AsIs

def addapt_numpy_array(numpy_array):
    return AsIs(tuple(numpy_array))

register_adapter(np.ndarray, addapt_numpy_array)

为了帮助一般使用 numpy，我依赖于 psycopg2 的脚本/库的默认插件是：

import numpy as np
from psycopg2.extensions import register_adapter, AsIs

def addapt_numpy_float64(numpy_float64):
    return AsIs(numpy_float64)

def addapt_numpy_int64(numpy_int64):
    return AsIs(numpy_int64)

def addapt_numpy_float32(numpy_float32):
    return AsIs(numpy_float32)

def addapt_numpy_int32(numpy_int32):
    return AsIs(numpy_int32)

def addapt_numpy_array(numpy_array):
    return AsIs(tuple(numpy_array))

register_adapter(np.float64, addapt_numpy_float64)
register_adapter(np.int64, addapt_numpy_int64)
register_adapter(np.float32, addapt_numpy_float32)
register_adapter(np.int32, addapt_numpy_int32)
register_adapter(np.ndarray, addapt_numpy_array)

否则即使是数字类型也会出现一些问题。

我从另一个那里得到了适配器技巧堆栈溢出条目 https://stackoverflow.com/questions/50626058/psycopg2-cant-adapt-type-numpy-int64.