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dataset_construct_other.py
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dataset_construct_other.py
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"""
Compilation of Other Useful Datasets
====================================
1. World Development Indicators Dataset
2. Atlas of Complexity Dataset
3. Penn World Table Dataset
Construct h5 datasets and pyeconlab objects
"""
import os
import gc
import shutil
import warnings
import pandas as pd
from pyeconlab import WDI, CIDAtlasDataConstructor, PENN
from dataset_info import SOURCE_DIR, TARGET_DATASET_DIR
#---------#
#-Control-#
#---------#
COMPILE_WDI = False
COMPILE_ATLAS = False #-!!-Requires AWS for 'Trade'-!!-# 'Trade Disabled'
COMPILE_PENN = True
#------------------------------#
#-World Development Indicators-#
#------------------------------#
if COMPILE_WDI:
wdi = WDI(source_dir=SOURCE_DIR['wdi'])
stata_wide_fln = wdi.to_stata(table_type="wide", target_dir=TARGET_DATASET_DIR['wdi']) # wdi_data_wide.dta
stata_long_fln = wdi.to_stata(table_type="long", target_dir=TARGET_DATASET_DIR['wdi']) # wdi_data_long.dta
hdf_fln = wdi.to_hdf(target_dir = TARGET_DATASET_DIR['wdi']) # wdi_data.h5
#-----------------------------#
#-Atlas of Complexity Dataset-#
#-----------------------------#
#-Countries Only Dataset-#
if COMPILE_ATLAS:
#-Values-#
print "[INFO] Processing VALUES Data ..."
for classification in ["SITCR2", "HS92"]:
print warnings.warn("This will not compile 'trade' data - just export and import data")
for dtype in ["export", "import"]: # -- !! -- Excluding "trade" -- !! -- due to memory constraints -- use stata -- #
print "Processing %s for %s data ..." % (classification, dtype)
atlas = CIDAtlasDataConstructor(source_dir=SOURCE_DIR['atlas'], trade_classification=classification, dtype=dtype, reduce_memory=True)
atlas.construct_standardized_dataset()
#-Store-#
startyear = atlas.dataset.year.min()
endyear = atlas.dataset.year.max()
fln = TARGET_DATASET_DIR["atlas"] + "cidatlas_%s_%s_%sto%s.h5"%(classification.lower(), dtype, startyear, endyear)
store = pd.HDFStore(fln, complevel=9, complib='zlib')
#-Country Value Data-#
atlas.countries_only()
#-Value-#
for level in [4,3,2,1]:
gc.collect()
print "[INFO] Saving Level %s ... " % level
if classification == "SITCR2":
productid = "sitc%s"%level
if dtype == "export":
idx = ["year", "eiso3c", productid]
elif dtype == "import":
idx = ["year", "iiso3c", productid]
else:
idx = ["year", "eiso3c", "iiso3c", productid]
if level != 4:
atlas.dataset[productid] = atlas.dataset["sitc4"].apply(lambda x: x[0:level])
if classification == "HS92":
productid = "hs%s"%level
if dtype == "export":
idx = ["year", "eiso3c", productid]
elif dtype == "import":
idx = ["year", "iiso3c", productid]
else:
idx = ["year", "eiso3c", "iiso3c", productid]
if level != 4:
atlas.dataset[productid] = atlas.dataset["hs4"].apply(lambda x: x[0:level])
#-Collapse Levels-#
countrydata = atlas.dataset[idx+["value"]].groupby(idx, as_index=False).sum()
store.put("L%s"%level, countrydata, format="table")
del countrydata
store.close()
del atlas
gc.collect()
#-RCA-#
print "[INFO] Processing RCA Data ..."
for classification in ["SITCR2", "HS92"]:
for dtype in ["export", "import"]:
print "Processing %s for %s data ..." % (classification, dtype)
atlas = CIDAtlasDataConstructor(source_dir=SOURCE_DIR['atlas'], trade_classification=classification, dtype=dtype)
atlas.construct_standardized_dataset()
#-Store-#
startyear = atlas.dataset.year.min()
endyear = atlas.dataset.year.max()
fln = TARGET_DATASET_DIR["atlas"] + "cidatlas_%s_%s_rca_%sto%s.h5"%(classification.lower(), dtype, startyear, endyear)
store = pd.HDFStore(fln, complevel=9, complib='zlib')
#-Country RCA Data-#
atlas.countries_only()
countrydata = atlas.dataset.copy(deep=True)
if classification == "SITCR2":
if dtype == "export":
idx = ["year", "eiso3c", "sitc4"]
elif dtype == "import":
idx = ["year", "iiso3c", "sitc4"]
if classification == "HS92":
if dtype == "export":
idx = ["year", "eiso3c", "hs4"]
elif dtype == "import":
idx = ["year", "iiso3c", "hs4"]
countrydata = countrydata.groupby(idx).sum()["rca"].reset_index()
store.put("L4", countrydata, format="table")
store.close()
del countrydata
gc.collect()
#--------------------------#
#-Penn World Table Dataset-#
#--------------------------#
if COMPILE_PENN:
print "[INFO] Processing PENN World Tables ... "
penn = PENN(source_dir=SOURCE_DIR['penn'])
penn.to_hdf(fl="penn_%s_%sto%s.h5"%(penn.version, penn.start_year, penn.end_year), target_dir=TARGET_DATASET_DIR["penn"])
penn.to_stata(fl="penn_%s_%sto%s.dta"%(penn.version, penn.start_year, penn.end_year), target_dir=TARGET_DATASET_DIR["penn"])