Frequently used functions for financial data analysis
Project description
x1
Frequently used functions for financial data analysis
Installation
pip install xone
Utilities
In[1]: from xone import utils
Convert anything to list.
- If the input is clean, use
tolist()
directly. Some functions requireslist
as input,tolist()
is to standardize all inputs for them.
In[2]: ticker = 'BHP AU'
In[3]: list_of_tickers = tolist(ticker)
In[4]: list_of_tickers
Out[4]: ['BHP AU']
In[5]: raw_price = [31.08, 31.10, 31.11, 31.07, 31.04, 31.04]
In[6]: price = utils.tolist(raw_price)
In[7]: price
Out[7]: [31.08, 31.10, 31.11, 31.07, 31.04, 31.04]
- If the input is list of tuples / lists / any weird combination, use
flatten()
:
In[8]: raw_volume = [(10166, 69981), [14343, 10096], 11506, 9718]
In[9]: volume = utils.flatten(raw_volume)
In[10]: volume
Out[10]: [10166, 69981, 14343, 10096, 11506, 9718]
Order preserving DataFrame construction from list of dict
.
Prior to Python 3.7, dict
is not ordered like OrderedDict
.
Passing dict
directly to DataFrame constructor will make the columns sorted by alphabets.
In[11]: import pandas as pd
In[12]: data_list = [
dict(sid=1, symbol='1 HK', price=88.8),
dict(sid=700, symbol='700 HK', price=350.),
]
In[13]: pd.DataFrame(data_list)
Out[13]:
price sid symbol
0 88.80 1 1 HK
1 350.00 700 700 HK
to_frame
makes sure the order of inputs will be kept:
In[14]: utils.to_frame(data_list)
Out[14]:
sid symbol price
0 1 1 HK 88.80
1 700 700 HK 350.00
Files
In[15]: from xone import files
Automatic check and create path and save files:
In[16]: DATA_PATH = '/data/Bloomberg'
In[17]: data_file = f'{DATA_PATH}/{ticker.split()[-1]}/{ticker}/2018-09-10.parq'
In[18]: sample = pd.DataFrame(
data=dict(price=price, volume=volume),
index=pd.DatetimeIndex(
start='2018-09-10T10:10:00', periods=6, freq='min'
).tz_localize('Australia/Sydney'),
)
In[19]: sample
Out[19]:
price volume
2018-09-10 10:10:00+10:00 31.08 10166
2018-09-10 10:11:00+10:00 31.10 69981
2018-09-10 10:12:00+10:00 31.11 14343
2018-09-10 10:13:00+10:00 31.07 10096
2018-09-10 10:14:00+10:00 31.04 11506
2018-09-10 10:15:00+10:00 31.04 9718
create_folder
checks folder existence and create all parent folders for the target folder.
In[20]: files.create_folder(data_file, is_file=True)
In[21]: sample.to_parquet(data_file)
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