V0.1.9b0

CEDA/__init__.py

@@ -1,7 +1,7 @@
 import sys
 import os
 
-__version__ = "0.1.9a"
+__version__ = "0.1.9b"
 __author__ = "Terence Lau"
 
 

CEDA/macroecon/eu.py

@@ -872,6 +872,11 @@ def Consumer_Opinion_Survey():
     description = "Consumer opinion surveys, Monthly, Seasonally Adjusted"
     return df, name_list, description
 
+def EU_EPU_Monthly():
+    df = pd.read_excel("https://www.policyuncertainty.com/media/Europe_Policy_Uncertainty_Data.xlsx")[:-1]
+    df['Date']=pd.to_datetime(df['Year'].apply(str).str.cat(df['Month'].apply(int).apply(str),sep='-'), format='%Y-%m')
+    df = df[["Date", "European_News_Index", "Germany_News_Index", "Italy_News_Index", "UK_News_Index", "France_News_Index"]]
+    return df
 
 class ecb_data(object):
     def __init__(self, url=url["ecb"]):

CEDA/macroecon/us.py

@@ -1092,4 +1092,16 @@ def Leading_Indicators_OECD(startdate = "1950-01", enddate = "2021-05"):
     df = pd.merge_asof(df_cli, df_bci, on = "Date")
     df = pd.merge_asof(df, df_cci, on = "Date")
     
+    return df
+
+def US_EPU_Monthly():
+    df = pd.read_excel("https://www.policyuncertainty.com/media/US_Policy_Uncertainty_Data.xlsx")[:-1]
+    df['Date']=pd.to_datetime(df['Year'].apply(str).str.cat(df['Month'].apply(int).apply(str),sep='-'), format='%Y-%m')
+    df = df[["Date", "US_Three_Component_Index", "US_EPU"]]
+    return df
+
+def US_EPU_Daily():
+    df = pd.read_csv("https://www.policyuncertainty.com/media/All_Daily_Policy_Data.csv")[:-1]
+    df['Date']=pd.to_datetime(df['year'].apply(str).str.cat(df['month'].apply(str),sep='-').apply(str).str.cat(df['day'].apply(str),sep='-'), format='%Y-%m-%d')
+    df = df.drop(["year", "month", "day"], axis=1)
     return df

setup.py

@@ -2,7 +2,7 @@ from setuptools import setup, find_packages
 import os
 setup(
     name = "CEDApy",
-    version = "0.1.9a",
+    version = "0.1.9b",
     keywords = "quantitative economic data",
     long_description = open(
     os.path.join(