Python error when calling column data from Pandas DataFrame

I practiced importing stock market data from Google Finance into a Pandas DataFrame:

import pandas as pd
from pandas import Series

path = 'http://www.google.com/finance/historical?cid=542029859096076&startdate=Sep+22%2C+2001&enddate=Sep+20%2C+2016&num=30&ei=3HvhV4n3D8XGmAGp4q74Ag&output=csv'
df = pd.read_csv(path)

So far, so good, and df also shows the complete dataset I need.

However, when calling certain columns, for example

df['Date']

Python shows error codes below:

Traceback (most recent call last):

  File "<ipython-input-31-cb486dd31fbc>", line 1, in <module>
    df['Date']

  File "/Users/Username/anaconda/lib/python3.5/site-packages/pandas/core/frame.py", line 1997, in __getitem__
    return self._getitem_column(key)

  File "/Users/Username/anaconda/lib/python3.5/site-packages/pandas/core/frame.py", line 2004, in _getitem_column
    return self._get_item_cache(key)

  File "/Users/Username/anaconda/lib/python3.5/site-packages/pandas/core/generic.py", line 1350, in _get_item_cache
    values = self._data.get(item)

  File "/Users/Username/anaconda/lib/python3.5/site-packages/pandas/core/internals.py", line 3290, in get
    loc = self.items.get_loc(item)

  File "/Users/Username/anaconda/lib/python3.5/site-packages/pandas/indexes/base.py", line 1947, in get_loc
    return self._engine.get_loc(self._maybe_cast_indexer(key))

  File "pandas/index.pyx", line 137, in pandas.index.IndexEngine.get_loc (pandas/index.c:4154)

  File "pandas/index.pyx", line 159, in pandas.index.IndexEngine.get_loc (pandas/index.c:4018)

  File "pandas/hashtable.pyx", line 675, in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:12368)

  File "pandas/hashtable.pyx", line 683, in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:12322)

KeyError: 'Date'

On the other hand, other columns like df ['High'] are ok. Anyway, can I fix this problem?

+4
source share
1 answer

This CSV file contains the specification signature (Byte Order Mark) , so try to do it like this:

df = pd.read_csv(path, encoding='utf-8-sig')

( @jezrael):

In [11]: print(df.columns.tolist())
['\ufeffDate', 'Open', 'High', 'Low', 'Close', 'Volume']

:, @ayhan , 0.19.0 Pandas :

pd.read_csv(), - BOM , GH4793

+5

Source: https://habr.com/ru/post/1655231/


All Articles