Index

_

__init__() (pd_utils.regby.ResultCounter method)

A

add_missing_group_rows() (in module pd_utils.filldata) apply_func_to_unique_and_merge() (in module pd_utils.merge) ascending (pd_utils.merge.groupby_index parameter), [1] averages() (in module pd_utils.transform)

avgonly (pd_utils.port.portfolio_averages parameter), [1] avgvars (pd_utils.port.portfolio_averages parameter), [1] (pd_utils.transform.averages parameter), [1] axis_locations_in_legend (pd_utils.plot.plot_multi_axis parameter)

B

backend (pd_utils.merge.left_merge_latest parameter), [1] bot (pd_utils.transform.winsorize parameter), [1] byvars (pd_utils.cum.cumulate parameter), [1] (pd_utils.filldata.fill_excluded_rows parameter), [1] (pd_utils.merge.groupby_index parameter), [1] (pd_utils.merge.groupby_merge parameter), [1] (pd_utils.port.long_short_portfolio parameter), [1] (pd_utils.port.portfolio parameter), [1] (pd_utils.port.portfolio_averages parameter), [1] (pd_utils.transform.averages parameter), [1] (pd_utils.transform.var_change_by_groups parameter), [1] (pd_utils.transform.winsorize parameter), [1]

C

col (pd_utils.transform.state_abbrev parameter), [1] colindex (pd_utils.transform.long_to_wide parameter), [1] colindex_only (pd_utils.transform.long_to_wide parameter), [1] colored_axes (pd_utils.plot.plot_multi_axis parameter) cols (pd_utils.corr.formatted_corr_df parameter), [1] (pd_utils.plot.plot_multi_axis parameter) (pd_utils.query.select_rows_by_condition_on_columns parameter), [1] (pd_utils.transform.join_col_strings parameter), [1] column_names (pd_utils.testing.to_copy_paste parameter), [1] condition (pd_utils.query.select_rows_by_condition_on_columns parameter), [1] cons (pd_utils.regby.reg_by parameter), [1]

convert_sas_date_to_pandas_date() (in module pd_utils.datetime_utils) count (pd_utils.port.portfolio_averages parameter), [1] (pd_utils.transform.averages parameter), [1] create_windows() (in module pd_utils.cum) csv (pd_utils.load.load_sas parameter), [1] cumulate() (in module pd_utils.cum) cumvars (pd_utils.cum.cumulate parameter), [1] custom_business_day (pd_utils.datetime_utils.expand_time parameter), [1] cutdf (pd_utils.port.portfolio parameter), [1] (pd_utils.port.portfolio_averages parameter), [1] cutoffs (pd_utils.port.portfolio parameter), [1]

D

date (pd_utils.datetime_utils.year_month_from_date parameter), [1] datevar (pd_utils.datetime_utils.expand_months parameter), [1] (pd_utils.datetime_utils.expand_time parameter), [1] (pd_utils.transform.var_change_by_groups parameter), [1] df (pd_utils.corr.formatted_corr_df parameter), [1] (pd_utils.cum.cumulate parameter), [1] (pd_utils.datetime_utils.expand_months parameter), [1] (pd_utils.datetime_utils.expand_time parameter), [1] (pd_utils.datetime_utils.year_month_from_date parameter), [1] (pd_utils.filldata.add_missing_group_rows parameter), [1] (pd_utils.filldata.fill_excluded_rows parameter), [1] (pd_utils.merge.groupby_index parameter), [1] (pd_utils.merge.groupby_merge parameter), [1] (pd_utils.merge.left_merge_latest parameter), [1] (pd_utils.plot.plot_multi_axis parameter) (pd_utils.port.long_short_portfolio parameter), [1] (pd_utils.port.portfolio parameter), [1] (pd_utils.port.portfolio_averages parameter), [1] (pd_utils.query.select_rows_by_condition_on_columns parameter), [1] (pd_utils.regby.reg_by parameter), [1] (pd_utils.testing.to_copy_paste parameter), [1] (pd_utils.transform.averages parameter), [1] (pd_utils.transform.join_col_strings parameter), [1] (pd_utils.transform.long_to_wide parameter), [1] (pd_utils.transform.state_abbrev parameter), [1] (pd_utils.transform.var_change_by_groups parameter), [1] (pd_utils.transform.winsorize parameter), [1]

df2 (pd_utils.merge.left_merge_latest parameter), [1] df_for_reg() (in module pd_utils.regby) df_list (pd_utils.query.sql parameter), [1] df_types_dict() (in module pd_utils.optimize.dftypes) drop_missing_group_rows() (in module pd_utils.filldata)

E

estimate_time() (in module pd_utils.timer)

expand_months() (in module pd_utils.datetime_utils) expand_time() (in module pd_utils.datetime_utils)

F

filepath (pd_utils.load.load_sas parameter), [1] fill_excluded_rows() (in module pd_utils.filldata) fill_limit (pd_utils.filldata.add_missing_group_rows parameter), [1] fill_method (pd_utils.filldata.add_missing_group_rows parameter), [1] fillna_by_groups() (in module pd_utils.filldata) fillna_by_groups_and_keep_one_per_group() (in module pd_utils.filldata) fillna_kwargs (pd_utils.filldata.fill_excluded_rows parameter), [1]

fillvars (pd_utils.filldata.fill_excluded_rows parameter), [1] flatten (pd_utils.transform.averages parameter), [1] formatted_corr_df() (in module pd_utils.corr) freq (pd_utils.datetime_utils.expand_time parameter), [1] func (pd_utils.merge.apply_func_to_unique_and_merge parameter), [1] func_args (pd_utils.merge.groupby_merge parameter), [1] func_str (pd_utils.merge.groupby_merge parameter), [1]

G

grossify (pd_utils.cum.cumulate parameter), [1] group_id_cols (pd_utils.filldata.add_missing_group_rows parameter), [1] groupby_index() (in module pd_utils.merge) groupby_merge() (in module pd_utils.merge)

groupvar (pd_utils.port.portfolio parameter), [1] (pd_utils.port.portfolio_averages parameter), [1] (pd_utils.regby.reg_by parameter), [1] groupvars (pd_utils.transform.long_to_wide parameter), [1]

I

i (pd_utils.timer.estimate_time parameter)

index (pd_utils.testing.to_copy_paste parameter), [1] intermediate_periods (pd_utils.datetime_utils.expand_time parameter), [1]

J

join_col_strings() (in module pd_utils.transform)

K

kwargs (pd_utils.plot.plot_multi_axis parameter)

L

left_datevar (pd_utils.merge.left_merge_latest parameter), [1] left_merge_latest() (in module pd_utils.merge) legend_kwargs (pd_utils.plot.plot_multi_axis parameter) length (pd_utils.timer.estimate_time parameter)

load_sas() (in module pd_utils.load) logic (pd_utils.query.select_rows_by_condition_on_columns parameter), [1] long_short_portfolio() (in module pd_utils.port) long_to_wide() (in module pd_utils.transform) low_memory (pd_utils.merge.left_merge_latest parameter), [1]

M

max_offset (pd_utils.merge.left_merge_latest parameter), [1] merge (pd_utils.regby.reg_by parameter), [1] method (pd_utils.cum.cumulate parameter), [1] module pd_utils pd_utils.corr pd_utils.cum pd_utils.datetime_utils pd_utils.filldata pd_utils.load pd_utils.merge pd_utils.optimize pd_utils.optimize.dftypes pd_utils.optimize.load pd_utils.optimize.typing pd_utils.plot pd_utils.port pd_utils.query pd_utils.regby pd_utils.testing pd_utils.timer pd_utils.transform pd_utils.utils

monthname (pd_utils.datetime_utils.year_month_from_date parameter), [1] mp (pd_utils.regby.reg_by parameter), [1] multiprocess (pd_utils.cum.cumulate parameter), [1] (pd_utils.port.portfolio parameter), [1]

N

newdate (pd_utils.datetime_utils.expand_time parameter), [1] newdatevar (pd_utils.datetime_utils.expand_months parameter), [1] ngroups (pd_utils.port.portfolio parameter), [1] (pd_utils.port.portfolio_averages parameter), [1]

non_group_id_cols (pd_utils.filldata.add_missing_group_rows parameter), [1] numlags (pd_utils.transform.var_change_by_groups parameter), [1]

O

on (pd_utils.merge.left_merge_latest parameter), [1] optimized_df() (in module pd_utils.optimize.dftypes)

ordinal() (in module pd_utils.plot) output (pd_utils.timer.estimate_time parameter)

P

pct (pd_utils.transform.winsorize parameter), [1] pd_utils module pd_utils.corr module pd_utils.cum module pd_utils.datetime_utils module pd_utils.filldata module pd_utils.load module pd_utils.merge module pd_utils.optimize module pd_utils.optimize.dftypes module pd_utils.optimize.load module pd_utils.optimize.typing module

pd_utils.plot module pd_utils.port module pd_utils.query module pd_utils.regby module pd_utils.testing module pd_utils.timer module pd_utils.transform module pd_utils.utils module periodvar (pd_utils.cum.cumulate parameter), [1] plot_multi_axis() (in module pd_utils.plot) portfolio() (in module pd_utils.port) portfolio_averages() (in module pd_utils.port) portvar (pd_utils.port.long_short_portfolio parameter), [1] (pd_utils.port.portfolio parameter), [1] (pd_utils.port.portfolio_averages parameter), [1]

Q

quant_cutoffs (pd_utils.port.portfolio parameter), [1]

query (pd_utils.query.sql parameter), [1]

R

read_csv_kwargs (pd_utils.load.load_sas parameter), [1] read_file() (in module pd_utils.optimize.load) reg_by() (in module pd_utils.regby) replace (pd_utils.cum.cumulate parameter), [1] (pd_utils.merge.groupby_merge parameter), [1]

ResultCounter (class in pd_utils.regby) retvars (pd_utils.port.long_short_portfolio parameter), [1] right_datevar (pd_utils.merge.left_merge_latest parameter), [1] rules (pd_utils.datetime_utils.USTradingCalendar attribute)

S

sasdates (pd_utils.datetime_utils.convert_sas_date_to_pandas_date parameter), [1] select_rows_by_condition_on_columns() (in module pd_utils.query) series (pd_utils.merge.apply_func_to_unique_and_merge parameter), [1] shiftvar (pd_utils.datetime_utils.expand_time parameter), [1] sortvars (pd_utils.merge.groupby_index parameter), [1] spacing (pd_utils.plot.plot_multi_axis parameter) split() (in module pd_utils.utils)

split_gen() (in module pd_utils.utils) sql() (in module pd_utils.query) start_time (pd_utils.timer.estimate_time parameter) state_abbrev() (in module pd_utils.transform) stderr (pd_utils.regby.reg_by parameter), [1] subset (pd_utils.merge.groupby_merge parameter), [1] (pd_utils.transform.winsorize parameter), [1]

T

time (pd_utils.cum.cumulate parameter), [1] (pd_utils.datetime_utils.expand_time parameter), [1] to_copy_paste() (in module pd_utils.testing) toabbrev (pd_utils.transform.state_abbrev parameter), [1]

top (pd_utils.transform.winsorize parameter), [1] top_minus_bot (pd_utils.port.long_short_portfolio parameter), [1] trade_days (pd_utils.datetime_utils.expand_months parameter), [1] tradedays() (in module pd_utils.datetime_utils)

U

USTradingCalendar (class in pd_utils.datetime_utils)

V

values (pd_utils.transform.long_to_wide parameter), [1]

var (pd_utils.transform.var_change_by_groups parameter), [1] var_change_by_groups() (in module pd_utils.transform)

W

window_mapping() (in module pd_utils.cum) winsorize() (in module pd_utils.transform)

wtvar (pd_utils.port.portfolio_averages parameter), [1] (pd_utils.transform.averages parameter), [1]

X

xvars (pd_utils.regby.reg_by parameter), [1]

Y

year_month_from_date() (in module pd_utils.datetime_utils) year_month_from_single_date() (in module pd_utils.datetime_utils)

yearname (pd_utils.datetime_utils.year_month_from_date parameter), [1] yvar (pd_utils.regby.reg_by parameter), [1]