尝试使用重命名函数重命名数据框架中的pandas列时出错

Question

我有一个数据框架，在那里我正在做一些货币计算。但是，当我以标准方式重命名列时，尽管我使用了重命名函数

，但仍然会显示相同的数据帧。

import pandas as pd
import matplotlib.pyplot as plt
import datetime
url1 = 'http://www.bankofcanada.ca/'
url2 = 'valet/observations/group/FX_RATES_DAILY/csv?start_date='
start_date = '2017-01-03'  
url = url1 + url2 + start_date  

rates = pd.read_csv(url, skiprows=39, index_col='date')
rates.index = pd.to_datetime(rates.index)  # assures data type to be a datetime
print("Print rates to the screen",rates)
#print index
print("Print index to the screen", rates.index)
days, currencies = rates.shape
codes = pd.read_csv(url, skiprows=10, usecols=[0,2],
nrows=currencies)
for i in range(currencies):
codes.iloc[i, 1] = codes.iloc[i, 1].split(' to Canadian')[0]
#date = rates.index[-1]  
#Make a series of just the rates of FXAUDCAD
FXAUDCAD_daily = pd.DataFrame(rates['FXAUDCAD'])
#Print FXAUDRATES to the screen
print(FXAUDCAD_daily)
#Calculate the MA using the rolling function with a window size of 1
FXAUDCAD_daily['rolling mean'] = FXAUDCAD_daily['FXAUDCAD'].rolling(1).mean()
#print out the new dataframe with calculation
print(FXAUDCAD_daily)
#Rename one of the data frame from FXAUDCAD to Exchange Rate
FXAUDCAD_daily.rename(columns={'FXAUDCAD':'rate'})
#print out the new dataframe with calculation
print(FXAUDCAD_daily)

Answer 1

重命名函数返回结果，但是您仍然需要像这样更新FXAUDCAD_daily:

FXAUDCAD_daily = FXAUDCAD_daily.rename(columns={'FXAUDCAD':'rate'})

也可以使用参数inplace=True。如果你想了解更多的信息，可以考虑看看这篇文章。

Answer 2

import pandas as pd
import matplotlib.pyplot as plt
import datetime
url1 = 'http://www.bankofcanada.ca/'
url2 = 'valet/observations/group/FX_RATES_DAILY/csv?start_date='
start_date = '2017-01-03'  
url = url1 + url2 + start_date  

rates = pd.read_csv(url, skiprows=39, index_col='date')
rates.index = pd.to_datetime(rates.index)  # assures data type to be a         
datetime
print("Print rates to the screen",rates)
#print index
print("Print index to the screen", rates.index)
days, currencies = rates.shape
codes = pd.read_csv(url, skiprows=10, usecols=[0,2],
nrows=currencies)
for i in range(currencies):
codes.iloc[i, 1] = codes.iloc[i, 1].split(' to Canadian')[0]
#date = rates.index[-1]  
#Make a series of just the rates of FXAUDCAD
FXAUDCAD_daily = pd.DataFrame(rates['FXAUDCAD'])
#Print FXAUDRATES to the screen
print(FXAUDCAD_daily)
#Calculate the MA using the rolling function with a window size of 1
FXAUDCAD_daily['rolling mean'] =         
FXAUDCAD_daily['FXAUDCAD'].rolling(1).mean()
#print out the new dataframe with calculation
print(FXAUDCAD_daily)
#Rename one of the data frame from FXAUDCAD to Exchange Rate
FXAUDCAD_daily.rename(columns={'FXAUDCAD':'rate'}, inplace=True)
#print out the new dataframe with calculation
print(FXAUDCAD_daily)