pandas

Stata-to-pandas utilities, used in nbstata.browse

Better stata-to-pandas

Improves on pystata.stata.pdataframe_from_data (and pystata.stata.pdataframe_from_frame) by making the pandas DataFrame index correspond to Stata observation numbers and also providing an option to output numeric values as strings using their Stata formats.

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source

better_dataframe_from_stata

 better_dataframe_from_stata (stfr, var, obs, selectvar, valuelabel,
                              missingval, sformat)

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source

better_pdataframe_from_data

 better_pdataframe_from_data (var=None, obs=None, selectvar=None,
                              valuelabel=False, missingval=None,
                              sformat=False)

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source

better_pdataframe_from_frame

 better_pdataframe_from_frame (stfr, var=None, obs=None, selectvar=None,
                               valuelabel=False, missingval=None,
                               sformat=False)

run_sfi("""\
sysuse uslifeexp2, clear
replace le = . if _n==5
replace year = 2022 if year==1900
format year %-ty
gen str_var = "test string" if _n!=5
gen date = dofy(year)
format date %td
gen double date_tc = cofd(date)
format date_tc %tc
gen double date_tC = Cofd(date)
format date_tC %tC""")
better_pdataframe_from_data().head()

(US life expectancy, 1900–1940)
(1 real change made, 1 to missing)
(1 real change made)
(1 missing value generated)

	year	le	str_var	date	date_tc	date_tC
1	2022	47.299999	test string	22646.0	1.956614e+12	1.956614e+12
2	1901	49.099998	test string	-21549.0	-1.861834e+12	-1.861834e+12
3	1902	51.500000	test string	-21184.0	-1.830298e+12	-1.830298e+12
4	1903	50.500000	test string	-20819.0	-1.798762e+12	-1.798762e+12
5	1904	NaN		-20454.0	-1.767226e+12	-1.767226e+12

better_pdataframe_from_data(sformat=True).head()

	year	le	str_var	date	date_tc	date_tC
1	2022	47.3	test string	01jan2022	01jan2022 00:00:00	01jan2022 00:00:00
2	1901	49.1	test string	01jan1901	01jan1901 00:00:00	01jan1901 00:00:00
3	1902	51.5	test string	01jan1902	01jan1902 00:00:00	01jan1902 00:00:00
4	1903	50.5	test string	01jan1903	01jan1903 00:00:00	01jan1903 00:00:00
5	1904	.		01jan1904	01jan1904 00:00:00	01jan1904 00:00:00