In [7]:
sp500 = fred.get_series(series_id='SP500')
sp500.plot(figsize=(10, 5), title='S&P 500', lw=2)
plt.show()
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import plotly.express as px
import time
plt.style.use('fivethirtyeight')
!pip install fredapi
Requirement already satisfied: fredapi in c:\users\hunte\anaconda3\lib\site-packages (0.5.0) Requirement already satisfied: pandas in c:\users\hunte\anaconda3\lib\site-packages (from fredapi) (1.4.2) Requirement already satisfied: numpy>=1.18.5 in c:\users\hunte\anaconda3\lib\site-packages (from pandas->fredapi) (1.21.5) Requirement already satisfied: pytz>=2020.1 in c:\users\hunte\anaconda3\lib\site-packages (from pandas->fredapi) (2021.3) Requirement already satisfied: python-dateutil>=2.8.1 in c:\users\hunte\anaconda3\lib\site-packages (from pandas->fredapi) (2.8.2) Requirement already satisfied: six>=1.5 in c:\users\hunte\anaconda3\lib\site-packages (from python-dateutil>=2.8.1->pandas->fredapi) (1.16.0)
# fetch api key
from tkinter import *
from tkinter import filedialog
from tkinter import Tk
import json
# We don't need the tkinter popup window
root = Tk()
root.withdraw()
filepath = filedialog.askopenfilename()
file = open(filepath, 'r')
credentials = json.load(file)
file.close()
fred_key = credentials['fred_api']
from fredapi import Fred
fred = Fred(api_key=fred_key)
sp_search = fred.search('S&P', order_by='popularity')
sp_search.head()
| id | realtime_start | realtime_end | title | observation_start | observation_end | frequency | frequency_short | units | units_short | seasonal_adjustment | seasonal_adjustment_short | last_updated | popularity | notes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| series id | |||||||||||||||
| BAMLH0A0HYM2 | BAMLH0A0HYM2 | 2024-03-28 | 2024-03-28 | ICE BofA US High Yield Index Option-Adjusted S... | 1996-12-31 | 2024-03-27 | Daily, Close | D | Percent | % | Not Seasonally Adjusted | NSA | 2024-03-28 08:51:11-05:00 | 92 | The ICE BofA Option-Adjusted Spreads (OASs) ar... |
| CSUSHPINSA | CSUSHPINSA | 2024-03-28 | 2024-03-28 | S&P CoreLogic Case-Shiller U.S. National Home ... | 1987-01-01 | 2024-01-01 | Monthly | M | Index Jan 2000=100 | Index Jan 2000=100 | Not Seasonally Adjusted | NSA | 2024-03-26 08:11:02-05:00 | 88 | For more information regarding the index, plea... |
| SP500 | SP500 | 2024-03-28 | 2024-03-28 | S&P 500 | 2014-03-28 | 2024-03-27 | Daily, Close | D | Index | Index | Not Seasonally Adjusted | NSA | 2024-03-27 19:11:00-05:00 | 83 | The observations for the S&P 500 represent the... |
| MEHOINUSA672N | MEHOINUSA672N | 2024-03-28 | 2024-03-28 | Real Median Household Income in the United States | 1984-01-01 | 2022-01-01 | Annual | A | 2022 CPI-U-RS Adjusted Dollars | 2022 CPI-U-RS Adjusted $ | Not Seasonally Adjusted | NSA | 2023-09-12 13:48:02-05:00 | 83 | Household data are collected as of March. As ... |
| BAMLH0A0HYM2EY | BAMLH0A0HYM2EY | 2024-03-28 | 2024-03-28 | ICE BofA US High Yield Index Effective Yield | 1996-12-31 | 2024-03-27 | Daily, Close | D | Percent | % | Not Seasonally Adjusted | NSA | 2024-03-28 08:51:15-05:00 | 82 | This data represents the effective yield of th... |
sp500 = fred.get_series(series_id='SP500')
sp500.plot(figsize=(10, 5), title='S&P 500', lw=2)
plt.show()
unemp_df = fred.search('unemployment rate state', filter=('frequency','Monthly'))
unemp_df = unemp_df.query('seasonal_adjustment == "Seasonally Adjusted" and units == "Percent"')
unemp_df = unemp_df.loc[unemp_df['title'].str.contains('Unemployment Rate')]
all_results = []
for myid in unemp_df.index:
results = fred.get_series(myid)
results = results.to_frame(name=myid)
all_results.append(results)
time.sleep(0.1) # Don't request too fast and get blocked
uemp_results = pd.concat(all_results, axis=1)
cols_to_drop = []
for i in uemp_results:
if len(i) > 4:
cols_to_drop.append(i)
uemp_results = uemp_results.drop(columns = cols_to_drop, axis=1)
uemp_results.shape
(1127, 52)
uemp_states = uemp_results.copy() #.drop('UNRATE', axis=1)
uemp_states = uemp_states.dropna()
id_to_state = unemp_df['title'].str.replace('Unemployment Rate in ','').to_dict()
uemp_states.columns = [id_to_state[c] for c in uemp_states.columns]
# Plot States Unemployment Rate
px.line(uemp_states)
ax = uemp_states.loc[uemp_states.index == '2023-12-01'].T \
.sort_values('2023-12-01') \
.plot(kind='barh', figsize=(8, 12), width=0.7, edgecolor='black',
title='Unemployment Rate by State, December 2023')
ax.legend().remove()
ax.set_xlabel('% Unemployed')
plt.show()
part_df = fred.search('participation rate state', filter=('frequency','Monthly'))
part_df = part_df.query('seasonal_adjustment == "Seasonally Adjusted" and units == "Percent"')
part_id_to_state = part_df['title'].str.replace('Labor Force Participation Rate for ','').to_dict()
all_results = []
for myid in part_df.index:
results = fred.get_series(myid)
results = results.to_frame(name=myid)
all_results.append(results)
time.sleep(0.1) # Don't request too fast and get blocked
part_states = pd.concat(all_results, axis=1)
part_states.columns = [part_id_to_state[c] for c in part_states.columns]
# Fix DC
uemp_states = uemp_states.rename(columns={'the District of Columbia':'District Of Columbia'})
# Put the uemp_states columns in alphabetical order
uemp_states = uemp_states.reindex(sorted(uemp_states.columns), axis=1)
fig, axs = plt.subplots(10, 5, figsize=(30, 30), sharex=True)
axs = axs.flatten()
i = 0
for state in uemp_states.columns:
if state in ["District Of Columbia","Puerto Rico"]:
continue
ax2 = axs[i].twinx()
uemp_states.query('index >= 2020 and index < 2022')[state] \
.plot(ax=axs[i], label='Unemployment')
part_states.query('index >= 2020 and index < 2022')[state] \
.plot(ax=ax2, label='Participation', color='red')
ax2.grid(False)
axs[i].set_title(state)
i += 1
plt.tight_layout()
plt.show()
fred.search('unemployment rate men')
| id | realtime_start | realtime_end | title | observation_start | observation_end | frequency | frequency_short | units | units_short | seasonal_adjustment | seasonal_adjustment_short | last_updated | popularity | notes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| series id | |||||||||||||||
| LNS14000031 | LNS14000031 | 2024-03-28 | 2024-03-28 | Unemployment Rate - 20 Yrs. & over, Black or A... | 1972-01-01 | 2024-02-01 | Monthly | M | Percent | % | Seasonally Adjusted | SA | 2024-03-08 08:03:14-06:00 | 56 | The series comes from the 'Current Population ... |
| LNU04000031 | LNU04000031 | 2024-03-28 | 2024-03-28 | Unemployment Rate - 20 Yrs. & over, Black or A... | 1972-01-01 | 2024-02-01 | Monthly | M | Percent | % | Not Seasonally Adjusted | NSA | 2024-03-08 08:02:27-06:00 | 5 | The series comes from the 'Current Population ... |
| LNS14000001 | LNS14000001 | 2024-03-28 | 2024-03-28 | Unemployment Rate - Men | 1948-01-01 | 2024-02-01 | Monthly | M | Percent | % | Seasonally Adjusted | SA | 2024-03-08 08:03:21-06:00 | 41 | The series comes from the 'Current Population ... |
| LNS13000001 | LNS13000001 | 2024-03-28 | 2024-03-28 | Unemployment Level - Men | 1948-01-01 | 2024-02-01 | Monthly | M | Thousands of Persons | Thous. of Persons | Seasonally Adjusted | SA | 2024-03-08 08:03:23-06:00 | 42 | The series comes from the 'Current Population ... |
| LNU04000001 | LNU04000001 | 2024-03-28 | 2024-03-28 | Unemployment Rate - Men | 1948-01-01 | 2024-02-01 | Monthly | M | Percent | % | Not Seasonally Adjusted | NSA | 2024-03-08 08:02:23-06:00 | 5 | The series comes from the 'Current Population ... |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| LRUN64MANZQ156S | LRUN64MANZQ156S | 2024-03-28 | 2024-03-28 | Unemployment Rate: Aged 15-64: Males for New Z... | 1986-01-01 | 2023-07-01 | Quarterly | Q | Percent | % | Seasonally Adjusted | SA | 2023-11-17 11:46:38-06:00 | 0 | OECD Descriptor ID: LRUN64MA OECD unit ID: PC ... |
| LRUN64MAFIA156N | LRUN64MAFIA156N | 2024-03-28 | 2024-03-28 | Unemployment Rate: Aged 15-64: Males for Finland | 1998-01-01 | 2022-01-01 | Annual | A | Percent | % | Not Seasonally Adjusted | NSA | 2023-04-20 16:23:13-05:00 | 0 | OECD Descriptor ID: LRUN64MA OECD unit ID: PC ... |
| LRUN64MAFIA156S | LRUN64MAFIA156S | 2024-03-28 | 2024-03-28 | Unemployment Rate: Aged 15-64: Males for Finland | 1998-01-01 | 2022-01-01 | Annual | A | Percent | % | Seasonally Adjusted | SA | 2023-04-20 16:23:13-05:00 | 0 | OECD Descriptor ID: LRUN64MA OECD unit ID: PC ... |
| LRUN64MAFIQ156N | LRUN64MAFIQ156N | 2024-03-28 | 2024-03-28 | Unemployment Rate: Aged 15-64: Males for Finland | 1998-01-01 | 2023-07-01 | Quarterly | Q | Percent | % | Not Seasonally Adjusted | NSA | 2024-01-12 14:44:32-06:00 | 0 | OECD Descriptor ID: LRUN64MA OECD unit ID: PC ... |
| LRUNTTMAFIA156N | LRUNTTMAFIA156N | 2024-03-28 | 2024-03-28 | Unemployment Rate: Aged 15 and over: Males for... | 1998-01-01 | 2022-01-01 | Annual | A | Percent | % | Not Seasonally Adjusted | NSA | 2023-04-20 16:23:32-05:00 | 0 | OECD Descriptor ID: LRUNTTMA OECD unit ID: PC ... |
1000 rows × 15 columns
unemp_men = fred.get_series(series_id='LNS14000001')
unemp_men.plot(figsize=(10, 5), title='Unemployment Rate Men', lw=2)
plt.show()
fred.search('unemployment rate women')
| id | realtime_start | realtime_end | title | observation_start | observation_end | frequency | frequency_short | units | units_short | seasonal_adjustment | seasonal_adjustment_short | last_updated | popularity | notes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| series id | |||||||||||||||
| LNS14000002 | LNS14000002 | 2024-03-28 | 2024-03-28 | Unemployment Rate - Women | 1948-01-01 | 2024-02-01 | Monthly | M | Percent | % | Seasonally Adjusted | SA | 2024-03-08 08:03:17-06:00 | 51 | To obtain estimates of women worker employment... |
| LNU04000002 | LNU04000002 | 2024-03-28 | 2024-03-28 | Unemployment Rate - Women | 1948-01-01 | 2024-02-01 | Monthly | M | Percent | % | Not Seasonally Adjusted | NSA | 2024-03-08 08:02:28-06:00 | 4 | To obtain estimates of women worker employment... |
| LNS13000002 | LNS13000002 | 2024-03-28 | 2024-03-28 | Unemployment Level - Women | 1948-01-01 | 2024-02-01 | Monthly | M | Thousands of Persons | Thous. of Persons | Seasonally Adjusted | SA | 2024-03-08 08:03:23-06:00 | 41 | To obtain estimates of women worker employment... |
| LNS14000032 | LNS14000032 | 2024-03-28 | 2024-03-28 | Unemployment Rate - 20 Yrs. & over, Black or A... | 1972-01-01 | 2024-02-01 | Monthly | M | Percent | % | Seasonally Adjusted | SA | 2024-03-08 08:03:36-06:00 | 13 | To obtain estimates of women worker employment... |
| LNU04000032 | LNU04000032 | 2024-03-28 | 2024-03-28 | Unemployment Rate - 20 Yrs. & over, Black or A... | 1972-01-01 | 2024-02-01 | Monthly | M | Percent | % | Not Seasonally Adjusted | NSA | 2024-03-08 08:02:22-06:00 | 7 | To obtain estimates of women worker employment... |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| LRUN64FEJPA156N | LRUN64FEJPA156N | 2024-03-28 | 2024-03-28 | Unemployment Rate: Aged 15-64: Females for Japan | 1968-01-01 | 2022-01-01 | Annual | A | Percent | % | Not Seasonally Adjusted | NSA | 2023-02-14 12:01:09-06:00 | 0 | OECD Descriptor ID: LRUN64FE OECD unit ID: PC ... |
| LRUN64FEJPM156N | LRUN64FEJPM156N | 2024-03-28 | 2024-03-28 | Unemployment Rate: Aged 15-64: Females for Japan | 1968-01-01 | 2023-11-01 | Monthly | M | Percent | % | Not Seasonally Adjusted | NSA | 2024-01-12 14:49:01-06:00 | 0 | OECD Descriptor ID: LRUN64FE OECD unit ID: PC ... |
| LRUN64FEJPQ156N | LRUN64FEJPQ156N | 2024-03-28 | 2024-03-28 | Unemployment Rate: Aged 15-64: Females for Japan | 1968-01-01 | 2023-07-01 | Quarterly | Q | Percent | % | Not Seasonally Adjusted | NSA | 2023-11-17 12:26:53-06:00 | 0 | OECD Descriptor ID: LRUN64FE OECD unit ID: PC ... |
| LRUN64FEJPQ156S | LRUN64FEJPQ156S | 2024-03-28 | 2024-03-28 | Unemployment Rate: Aged 15-64: Females for Japan | 1970-01-01 | 2023-07-01 | Quarterly | Q | Percent | % | Seasonally Adjusted | SA | 2023-11-17 12:26:53-06:00 | 0 | OECD Descriptor ID: LRUN64FE OECD unit ID: PC ... |
| LRUN74FEUSA156N | LRUN74FEUSA156N | 2024-03-28 | 2024-03-28 | Unemployment Rate: Aged 15-74: Females for Uni... | 1981-01-01 | 2023-01-01 | Annual | A | Percent | % | Not Seasonally Adjusted | NSA | 2024-01-12 14:51:41-06:00 | 0 | OECD Descriptor ID: LRUN74FE OECD unit ID: PC ... |
1000 rows × 15 columns
unemp_women = fred.get_series(series_id='LNS14000002')
unemp_women.plot(figsize=(10, 5), title='Unemployment Rate Women', lw=2)
plt.show()
unemp_men = fred.get_series(series_id='LNS14000001')
unemp_men.plot(figsize=(10, 5), lw=2,label="Men")
unemp_women = fred.get_series(series_id='LNS14000002')
unemp_women.plot(figsize=(10, 5), title='Unemployment Rate Men and Women', lw=1,label="Women")
plt.legend()
plt.show()
