leosmigel / analyzingalpha Goto Github PK

Hi, I am very interesting about who did you get the S&P 500 historical component data because I have spent lots of time on it and finally found here.

I will appreciate with your answer. Thank you!

I came across your great series of articles recently.

They are a wonderful read.

KeyError Traceback (most recent call last)
in ()
6
7 # Get current S&P table and set header column
----> 8 sp500 = data[0].loc[1:,[0,1,6,7]]
9 columns = ['added_ticker', 'name', 'date', 'cik']
10 sp500.columns = columns

5 frames
/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py in getitem(self, key)
1760 except (KeyError, IndexError, AttributeError):
1761 pass
-> 1762 return self._getitem_tuple(key)
1763 else:
1764 # we by definition only have the 0th axis

/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py in _getitem_tuple(self, tup)
1287 continue
1288
-> 1289 retval = getattr(retval, self.name)._getitem_axis(key, axis=i)
1290
1291 return retval

/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py in _getitem_axis(self, key, axis)
1952 raise ValueError("Cannot index with multidimensional key")
1953
-> 1954 return self._getitem_iterable(key, axis=axis)
1955
1956 # nested tuple slicing

/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py in _getitem_iterable(self, key, axis)
1593 else:
1594 # A collection of keys
-> 1595 keyarr, indexer = self._get_listlike_indexer(key, axis, raise_missing=False)
1596 return self.obj._reindex_with_indexers(
1597 {axis: [keyarr, indexer]}, copy=True, allow_dups=True

/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py in _get_listlike_indexer(self, key, axis, raise_missing)
1551
1552 self._validate_read_indexer(
-> 1553 keyarr, indexer, o._get_axis_number(axis), raise_missing=raise_missing
1554 )
1555 return keyarr, indexer

/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py in _validate_read_indexer(self, key, indexer, axis, raise_missing)
1638 if missing == len(indexer):
1639 axis_name = self.obj._get_axis_name(axis)
-> 1640 raise KeyError(f"None of [{key}] are in the [{axis_name}]")
1641
1642 # We (temporarily) allow for some missing keys with .loc, except in

KeyError: "None of [Int64Index([0, 1, 6, 7], dtype='int64')] are in the [columns]"

Correct date is 2002-07-22

Some posts or folders contain some code that illustrate the idea. It is not ready to use (either no database or using other APIs that need to be verified on their credibility.

Could you please advise where to look for positions.securities.

https://github.com/selvanponraj/analyzingalpha/blob/711565fc471cfd59f084c54cac641d66147fcd61/risk-reward-ratio-for-stocks/equities-bracket-order.py#L4-L6

Regards
Selvan

Hi!
I was trying to download the free risk rate from the FRED and the following error is showed up:
ModuleNotFoundError Traceback (most recent call last)
in <cell line: 4>()
2 import fredapi as fa
3 import pandas as pd
----> 4 from local_settings import *
5 from local_settings import fred as settings
6 try:

ModuleNotFoundError: No module named 'local_settings'
Please could you help me in finding a solution for this issue??
Thanks in advance

Hello, I was reading https://alpaca.markets/learn/backtrader-01/ and tried to implement it, but the alpaca backtrader api seems to be outdated. Are you still using it or have you moved on from Alpaca and Backtrader?