updates readme with primary dealer statistics details

Author: deeleeramone

ny_fed/README.md

@@ -1,5 +1,104 @@
 # A Python Wrapper for the NY Federal Reserve
 
+## Primary Dealer Statistics
+
+This module (WIP) takes the raw data from the RESTful API and parses it into Pandas DataFrames.
+Individual time series can be returned, or grouped like the website.  All values are in millions of US dollars.
+
+https://www.newyorkfed.org/markets/counterparties/primary-dealers-statistics
+
+
+### How to Use
+
+Import it:
+
+```python
+from primary_dealer_statistics import search_pds_descriptions,get_pds_series,get_dealer_financing,DealerPositioning,Fails
+```
+
+Initialize the classes:
+
+```python
+dp = DealerPositioning()
+fails = Fails()
+```
+
+Search the descriptions:
+
+```python
+
+help(search_pds_descriptions)
+
+Signature: search_pds_descriptions(description: str = '') -> pandas.core.frame.DataFrame
+Docstring:
+Search for Primary Dealer Statistics descriptions. Results are case sensitive.
+
+Parameters
+----------
+description : str = ""
+    Keywords to search for. Results are case sensitive.
+
+Returns
+-------
+pd.DataFrame: Pandas DataFrame with Series IDs and descriptions.
+
+Examples
+--------
+>>> results = search_pds_descriptions(description = "FAILS")
+
+>>> results = search_pds_descriptions(description = "ASSET-BACKED")
+```
+
+```python
+search_pds_descriptions(description = "ASSET-BACKED").head(1)
+```
+
+| Description                                                                                                                                | Series ID   |
+|:-------------------------------------------------------------------------------------------------------------------------------------------|:------------|
+| Total - ASSET-BACKED SECURITIES: DEALER TRANSACTIONS WITH INTER-DEALER BROKERS. + ASSET-BACKED SECURITIES: DEALER TRANSACTIONS WITH OTHER. | PDABTOT     |
+
+
+Lookup individual series:
+
+```python
+get_pds_series('PDABTOT').tail(5)
+```
+
+| As Of Date   |   PDABTOT |
+|:-------------|----------:|
+| 2023-03-15   |      1818 |
+| 2023-03-22   |      1476 |
+| 2023-03-29   |      2765 |
+| 2023-04-05   |      2193 |
+| 2023-04-12   |      2097 |
+
+![Screenshot 2023-04-23 at 1 46 50 PM](https://user-images.githubusercontent.com/85772166/233865435-0c5a7d5a-aab4-49e9-b44e-bb30773515c5.png)
+
+```python
+dp.tips().tail(5)
+```
+
+| As Of Date   |   <= 2 Years |   > 2 Years <= 6 Years |   > 6 Years <= 11 Years |   > 11 Years |   Total TIPS |
+|:-------------|-------------:|-----------------------:|------------------------:|-------------:|-------------:|
+| 2023-03-15   |        11320 |                   6485 |                    1348 |          530 |        19683 |
+| 2023-03-22   |        10752 |                   6571 |                    1328 |          289 |        18940 |
+| 2023-03-29   |        10852 |                   6823 |                    1511 |          310 |        19496 |
+| 2023-04-05   |        12827 |                   7630 |                    1215 |          667 |        22339 |
+| 2023-04-12   |        11397 |                   7433 |                     570 |          290 |        19690 |
+
+```python
+fails.mbs_fails(mbs_class = 'c').tail(5)
+```
+
+| As Of Date   |   <2.5% |   2.5% |   3.0% |   3.5% |   4.0% |   4.5% |   5.0% |   5.5% |   6.0% |   >6.0% |
+|:-------------|--------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|--------:|
+| 2022-11-21   |   23468 |  49853 |  61728 |  43598 |  73162 | 121508 | 122199 |  92571 |  28146 |    3957 |
+| 2022-12-20   |   20403 |  47651 |  45153 |  33914 |  64548 |  81273 | 101005 |  96802 |  64589 |   25892 |
+| 2023-01-23   |   21386 |  44707 |  45006 |  34015 |  59571 |  77182 |  93820 |  83301 |  71046 |   32967 |
+| 2023-02-21   |   27093 |  49499 |  44586 |  36300 |  60985 |  89913 | 145910 | 102226 |  59099 |   19205 |
+| 2023-03-21   |   23438 |  42656 |  48508 |  33781 |  46644 |  79600 | 119420 |  95710 |  63744 |   18605 |
+
+
 ## RESTful API
 
 All data available from the RESTful API (https://markets.newyorkfed.org/static/docs/markets-api.html) is accessible via Python functions.