TUTORIAL: How to Create a Python GUI that will use the power of CHATgpt

Remote Data Access Tiingo Examples¶

Need a FREE TIINGO API key

In [52]:

import os
import pandas_datareader as pdr
import pandas as pd
import pandas
import matplotlib as mpl

%matplotlib inline

!pip3 install tiingo[pandas]¶

Set TIINGO_API_KEY in your environment variables in your .bash_profile, OR pass a dictionary with 'api_key' as a key into the TiingoClient.

In [53]:

config = {}

# To reuse the same HTTP Session across API calls (and have better performance), include a session key.
config['session'] = True

# If you don't have your API key as an environment variable,
# pass it in via a configuration dictionary.
config['api_key'] = "Your Tiingo API Key"

# Initialize
client = TiingoClient(config)

Get Ticker¶

In [54]:

ticker_metadata = client.get_ticker_metadata("GOOGL")

In [55]:

# Get latest prices, based on 3+ sources as JSON, sampled weekly

In [56]:

ticker_price = client.get_ticker_price("GOOGL", frequency="weekly")

In [57]:

# Get historical GOOGL prices from August 2017 as JSON, sampled daily

In [58]:

historical_prices = client.get_ticker_price("GOOGL",
                                            fmt='json',
                                            startDate='2019-08-01',
                                            endDate='2019-08-31',
                                            frequency='daily')

Create a text file and save results¶

In [59]:

with open("google_2019_file.txt", "w") as output:
  output.write(str(historical_prices))

In [37]:

# To receive results in pandas format, use the get_dataframe() method:
#Get a pd.DataFrame of the price history of a single symbol (default is daily):

In [38]:

ticker_history = client.get_dataframe("GOOGL")

In [39]:

ticker_history.head()

Out[39]:

	adjClose	adjHigh	adjLow	adjOpen	adjVolume	close	divCash	high	low	open	splitFactor	volume
date
2021-03-26 00:00:00+00:00	2024.73	2039.385	2003.85	2031.79	1398875	2024.73	0.0	2039.385	2003.85	2031.79	1.0	1398875

The method returns all of the available information on a symbol, such as open, high, low, close,¶

adjusted close, etc. This page in the tiingo api documentation lists the available information on each¶

symbol:¶

https://api.tiingo.com/docs/tiingo/daily#priceData.

Frequencies and start and end dates can be specified similarly to the json method above.

Get a pd.Series of only one column of the available response data by specifying one of the valid the 'metric_name' parameters:

In [40]:

ticker_history = client.get_dataframe("GOOGL", metric_name='adjClose')

In [41]:

ticker_history

Out[41]:

date
2021-03-26 00:00:00+00:00    2024.73
Name: adjClose, dtype: float64

In [42]:

#Get a pd.DataFrame for a list of symbols for a specified metric_name (default is adjClose if no
# metric_name is specified):

In [43]:

ticker_history2 = client.get_dataframe(['GOOGL', 'AAPL'],
                                      frequency='weekly',
                                      metric_name='volume',
                                      startDate='2017-01-01',
                                      endDate='2018-05-31')

In [44]:

ticker_history2

Out[44]:

	GOOGL	AAPL
2016-12-30 00:00:00+00:00	4983989	84828531
2017-01-06 00:00:00+00:00	6832004	103845468
2017-01-13 00:00:00+00:00	6572250	138810760
2017-01-20 00:00:00+00:00	4845240	116347987
2017-01-27 00:00:00+00:00	13053648	124748449
...	...	...
2018-05-04 00:00:00+00:00	9034426	252805668
2018-05-11 00:00:00+00:00	8725368	148266951
2018-05-18 00:00:00+00:00	8096281	99248752
2018-05-25 00:00:00+00:00	5698651	94394844
2018-06-01 00:00:00+00:00	10366549	92129925

75 rows × 2 columns

In [ ]: