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)
这是我的密码。当打印map_appliance_info(df_appliance)时,我收到错误-
文件“E:/iisc/code/try.py“,第69行,地图家电信息中 df_appliance_mapped=map_appliance_信息(df_appliance)
文件“E:/iisc/code/try.py设备信息,U线 对于范围内的i(len(df_appliance['sur_key'].values)):
文件“C:\Users\nidi\Anaconda2\lib\site packages\pandas\core\帧.py“,第1957行,ingetitem indexer=将\u转换为\u index_sliceable(self,key)
文件“C:\Users\nidi\Anaconda2\lib\site packages\pandas\core\索引.py“,第1658行,在convert_to_index_sliceable”中 elif isinstance(钥匙,兼容字符串类型)公司名称:
RuntimeError:调用Python对象时超出了最大递归深度
谁能帮忙吗。谢谢
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数据帧上调用^{印刷品
^{pr2}$如果
df_appliance_mapped
是第二个数据帧,则可以使用:相关问题 更多 >
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