在Pandas列重命名中引用ForLoop中的项目

Question

I have two pandas.DataFrame 's and I wish to rename a column named value , which exists in both, as the name of the dataframe:

#Debt level relative to currency strength
#preamble
import pandas as pd
import statsmodels.formula.api as sm #check that this is actually used
import os
import numpy as np

os.chdir('C:\\Users\\pineapple\\Desktop')

#function construction
def loader(y):
    return pd.read_csv(y, header='infer',  encoding="ISO-8859+-1")

def viewer(x):
    print(x.ix[:])

def delrow(x,y):
    return x[pd.notnull(x[y])]

#
names = ['currency', 'debt_ratio']

for i in names:
    i = loader(''+i+'.csv') #load data
    i = i.replace('..', np.NaN)

    for x in range(2007,2015):
        y = str(x)
        print(y)
        i=delrow(i, '' + y + ' [YR'+y+']') #deletes missing values
        i.rename(columns = {'' + y + ' [YR'+y+']': ''+ y +''}, inplace=True) #rename columns

    i = i.drop(['Series Name','Series Code', 'Country Name', \
         '1990 [YR1990]', '2000 [YR2000]' ], axis = 1)

    i = pd.melt(i, id_vars=['Country Code'],value_vars=['2007','2008','2009','2010','2011', \
    '2012','2013','2014']) #reshape

    i.rename(columns={'variable':'year', 'Country Code':'code'}, inplace=True)
    viewer(i)

    eval(i).rename(columns={'value':i}, inplace=True) #breaks here

    i['id'] = i['code'] + i['year']

    #output
    viewer(i)

This does not work - it fails to update the value column and messes up the format of the dataframe.

Answer 1

Change:

for i in names:
    i = loader(''+i+'.csv') #load data

To:

for name in names:
    i = loader(name + '.csv') #load data

Then do the rename with:

i.rename(columns={'value':name}, inplace=True)

Answer 2

You need to use eval :

MCVE

a = pd.DataFrame({'Value':[1,2,3,4]})
b = pd.DataFrame({'Value':[5,6,7,9]})

names = ['a','b']

for i in names:
    eval(i).rename(columns={'Value':i}, inplace=True)

print(a)

Output:

   a
0  1
1  2
2  3
3  4

print(b)

Output:

   b
0  5
1  6
2  7
3  9