调用Python对象时出现的最大递归深度 - 运行时错误

时间:2016-07-09 09:19:11

标签: python arrays excel numpy pandas

import pandas as pd
import xlsxwriter
import openpyxl as px
import numpy as np
from xlwt import Workbook
from os.path import expanduser

home = expanduser("~")

def read_survey():  
    df_appliance=pd.read_csv('C:/Users/nidi/Desktop/New folder/app_info.csv')
    df_appliance.fillna(0, inplace=True)
    return df_appliance

df_appliance=read_survey()

def map_appliance_info(df_appliance):

    oven_usage=[]
    #oven_type_radio=[]
    oven_type_micro=[]
    oven_type_oven=[]
    tube_light_count=[]
    led_count=[]
    incand_count=[]
    cfl_count=[]

    for i in range(len(df_appliance['sur_key'].values)):                   

        if df_appliance['oven-type'].values[i]=='radio':
            #oven_type_radio.append(1)
            oven_type_micro.append(0)
            oven_type_oven.append(0)
        elif df_appliance['oven-type'].values[i]=='micro':
            #oven_type_radio.append(0)
            oven_type_micro.append(1)
            oven_type_oven.append(0)
        elif df_appliance['oven-type'].values[i]=='oven':
            #oven_type_radio.append(0)
            oven_type_micro.append(0)
            oven_type_oven.append(1)
        else:
            #oven_type_radio.append(0)
            oven_type_micro.append(0)
            oven_type_oven.append(0)

        if df_appliance['oven-ousg'].values[i]=='little':
            oven_usage.append(1)
        elif df_appliance['oven-ousg'].values[i]=='defrost':
            oven_usage.append(5)
        elif df_appliance['oven-ousg'].values[i]=='mod':
            oven_usage.append(12)
        elif df_appliance['oven-ousg'].values[i]=='ext':
            oven_usage.append(30)
        else:
            oven_usage.append(0)

        #return df_appliance_mapped

        df_appliance_mapped = map_appliance_info(df_appliance)

result=np.array(df_appliance_mapped)

这是我的代码。当打印map_appliance_info(df_appliance)时,我收到错误 -

文件" E:/iisc/code/try.py",第69行,在map_appliance_info中     df_appliance_mapped = map_appliance_info(df_appliance)

文件" E:/iisc/code/try.py",第35行,在map_appliance_info中     for i in range(len(df_appliance [' sur_key']。values)):

文件" C:\ Users \ nidi \ Anaconda2 \ lib \ site-packages \ pandas \ core \ frame.py",第1957行, getitem     indexer = convert_to_index_sliceable(self,key)

文件" C:\ Users \ nidi \ Anaconda2 \ lib \ site-packages \ pandas \ core \ indexing.py",第1658行,在convert_to_index_sliceable中     elif isinstance(key,compat.string_types):

RuntimeError:调用Python对象时超出了最大递归深度

任何人都可以提供帮助。感谢

1 个答案:

答案 0 :(得分:0)

由于您正在调用pd.read_excel,因此必须安装Pandas。 因此,合并数据的最简单方法是在两个DataFrame上调用pd.merge

import pandas as pd

df1 = pd.DataFrame({0: [1, 1, 0, 0], 1: [0, 0, 1, 1], 2: [1, 2, 1, 5], 3: [1, 2, 3, 4]})
df2 = pd.DataFrame({0: [0, 1, 1, 0], 1: [1, 0, 0, 1], 2: [1, 2, 1, 5]})
result = pd.merge(df2, df1, on=[0,1,2])
print(result.values)

打印

[[0 1 1 3]
 [1 0 2 2]
 [1 0 1 1]
 [0 1 5 4]]

如果df_appliance_mapped是第二个DataFrame,您可以使用:

first_df = pd.read_excel('E:/iisc/code/energy_usage_appliance.xlsx',0,header=None)
result = pd.merge(df_appliance_mapped, first_df, on=[0,1,2])