AttributeError: 'tuple' object has no attribute 'lower'

Question

I wanted to specify the format of the date because it\'s in European format(Or else the dates will not be in order after I make it as index column). I did exactly from the t

Answer 1

You have double brackets in the columns name.

Also why not let pandas work for you? Example,

EDIT: since you don't want the GMT part to be taken into account, I removed it with a list comprehension

import pandas as pd

df = pd.read_csv("date_t.csv")

print(df)
df.columns = ['date', 'open','high','low','close','volume']

df['date'] = pd.to_datetime([x[:-9] for x in df['date'].squeeze().tolist()], dayfirst=True)

df.set_index('date', inplace=True)

print(df)

EDIT 2: explanation of the line [x[:-9] for x in df['date'].squeeze().tolist()]

df['date'].squeeze() -> squeeze dataframe column in a series

df['date'].squeeze().tolist() -> turn in into a list

[x[:-9] for x in df['date'].squeeze().tolist()] -> for each date in the list keep only the elements until the 9th counting from the end, meaning remove the GMT part

From your subset data, this is what I get. Pandas is smart enough to understand the GMT-0500 and convert the dates taking this into account.

                              1        2        3        4        5      6
0  01.01.2015 00:00:00.000 GMT-0500  0.94821  0.94821  0.94821  0.94821  0
1  01.01.2015 01:00:00.000 GMT-0500  0.94821  0.94821  0.94821  0.94821  0
2  01.01.2015 02:00:00.000 GMT-0500  0.94821  0.94821  0.94821  0.94821  0
3  01.01.2015 03:00:00.000 GMT-0500  0.94821  0.94821  0.94821  0.94821  0
4  01.01.2015 04:00:00.000 GMT-0500  0.94821  0.94821  0.94821  0.94821  0
                        open     high      low    close  volume
date                                                           
2015-01-01 00:00:00  0.94821  0.94821  0.94821  0.94821     0.0
2015-01-01 01:00:00  0.94821  0.94821  0.94821  0.94821     0.0
2015-01-01 02:00:00  0.94821  0.94821  0.94821  0.94821     0.0
2015-01-01 03:00:00  0.94821  0.94821  0.94821  0.94821     0.0
2015-01-01 04:00:00  0.94821  0.94821  0.94821  0.94821     0.0