How to name a dataframe column filled by numpy array?

Question

I am filling a DataFrame by transposing some numpy array :

    for symbol in syms[:5]:
    price_p = Share(symbol)
    closes_p = [c['Close'] for c in price_p.get_historical(startdate_s, enddate_s)] 
    dump = np.array(closes_p)
    na_price_ar.append(dump)
    print symbol
df = pd.DataFrame(na_price_ar).transpose()

df, the DataFrame is well filled however, the column name are 0,1,2...,5 I would like to rename them with the value of the element syms[:5]. I googled it and I found this:

    for symbol in syms[:5]:
    df.rename(columns={ ''+ str(i) + '' : symbol}, inplace=True)
    i = i+1

But if I check the variabke df I still have the same column name. Any ideas ?

unutbu · Accepted Answer · 2016-08-11 11:04:17Z

3

Instead of using a list of arrays and transposing, you could build the DataFrame from a dict whose keys are symbols and whose values are arrays of column values:

import numpy as np
import pandas as pd
np.random.seed(2016)
syms = 'abcde'
na_price_ar = {}
for symbol in syms[:5]:
    # price_p = Share(symbol)
    # closes_p = [c['Close'] for c in price_p.get_historical(startdate_s, enddate_s)] 
    # dump = np.array(closes_p)
    dump = np.random.randint(10, size=3)
    na_price_ar[symbol] = dump
    print(symbol)

df = pd.DataFrame(na_price_ar)
print(df)

yields

   a  b  c  d  e
0  3  3  8  2  4
1  7  8  7  6  1
2  2  4  9  3  9

answered Aug 11, 2016 at 11:04

unutbu

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Comments

jezrael · Accepted Answer · 2016-08-11 11:01:31Z

0

You can use:

na_price_ar = [['A','B','C'],[0,2,3],[1,2,4],[5,2,3],[8,2,3]]

syms = ['q','w','e','r','t','y','u']
df = pd.DataFrame(na_price_ar, index=syms[:5]).transpose()
print (df)
   q  w  e  r  t
0  A  0  1  5  8
1  B  2  2  2  2
2  C  3  4  3  3

answered Aug 11, 2016 at 11:01

jezrael

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Comments

Stefano Fedele · Accepted Answer · 2016-08-12 13:18:35Z

0

You may use as dictionary key into the .rename() method the df.columns[ number ] statement

dic = {'a': [4, 1, 3, 1], 'b': [4, 2, 1, 4], 'c': [5, 7, 9, 1], 'd': [4, 1, 3, 1], 'e': [5, 2, 6, 0]}
df = pd.DataFrame(dic)
number = 0
for symbol in syms[:5]:
    df.rename( columns = { df.columns[number]: symbol}, implace = True)
    number = number + 1

and the result is

   i  f  g  h  i
0  4  4  5  4  5
1  1  2  7  1  2
2  3  1  9  3  6
3  1  4  1  1  0

answered Aug 12, 2016 at 13:18

Stefano Fedele

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