Using pandas with Large Data Sets

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1		date	number_of_game	day_of_week	v_name	v_league	v_game_number	h_name	h_league	h_game_number	v_score	h_score	length_outs	day_night	completion	forefeit	protest	park_id	attendance	length_minutes	v_line_score	h_line_score	v_at_bats	v_hits	v_doubles	v_triples	v_homeruns	v_rbi	v_sacrifice_hits	v_sacrifice_flies	v_hit_by_pitch	v_walks	v_intentional walks	v_strikeouts	v_stolen_bases	v_caught_stealing	v_grounded_into_double	v_first_catcher_interference	v_left_on_base	v_pitchers_used	v_individual_earned_runs	v_team_earned_runs	v_wild_pitches	v_balks	v_putouts	v_assists	v_errors	v_passed_balls	v_double_plays	v_triple_plays	h_at_bats	h_hits	h_doubles	h_triples	h_homeruns	h_rbi	h_sacrifice_hits	h_sacrifice_flies	h_hit_by_pitch	h_walks	h_intentional walks	h_strikeouts	h_stolen_bases	h_caught_stealing	h_grounded_into_double	h_first_catcher_interference	h_left_on_base	h_pitchers_used	h_individual_earned_runs	h_team_earned_runs	h_wild_pitches	h_balks	h_putouts	h_assists	h_errors	h_passed_balls	h_double_plays	h_triple_plays	hp_umpire_id	hp_umpire_name	1b_umpire_id	1b_umpire_name	2b_umpire_id	2b_umpire_name	3b_umpire_id	3b_umpire_name	lf_umpire_id	lf_umpire_name	rf_umpire_id	rf_umpire_name	v_manager_id	v_manager_name	h_manager_id	h_manager_name	winning_pitcher_id	winning_pitcher_name	losing_pitcher_id	losing_pitcher_name	saving_pitcher_id	saving_pitcher_name
2	0	18710504	0	Thu	CL1	na	1	FW1	na	1	0	2	54.0	D	NaN	NaN	NaN	FOR01	200.0	120.0	0	10010000	30.0	4.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	-1.0	6.0	1.0	-1.0	-1.0	-1.0	4.0	1.0	1.0	1.0	0.0	0.0	27.0	9.0	0.0	3.0	0.0	0.0	31.0	4.0	1.0	0.0	0.0	2.0	0.0	0.0	0.0	1.0	-1.0	0.0	0.0	-1.0	-1.0	-1.0	3.0	1.0	0.0	0.0	0.0	0.0	27.0	3.0	3.0	1.0	1.0	0.0	boakj901	John Boake	NaN	(none)	NaN	(none)	NaN	(none)	NaN	(none)	NaN	(none)	paboc101	Charlie Pabor	lennb101	Bill Lennon	mathb101	Bobby Mathews	prata101	Al Pratt	NaN	(none)
3	1	18710505	0	Fri	BS1	na	1	WS3	na	1	20	18	54.0	D	NaN	NaN	NaN	WAS01	5000.0	145.0	107000435	640113030	41.0	13.0	1.0	2.0	0.0	13.0	0.0	0.0	0.0	18.0	-1.0	5.0	3.0	-1.0	-1.0	-1.0	12.0	1.0	6.0	6.0	1.0	0.0	27.0	13.0	10.0	1.0	2.0	0.0	49.0	14.0	2.0	0.0	0.0	11.0	0.0	0.0	0.0	10.0	-1.0	2.0	1.0	-1.0	-1.0	-1.0	14.0	1.0	7.0	7.0	0.0	0.0	27.0	20.0	10.0	2.0	3.0	0.0	dobsh901	Henry Dobson	NaN	(none)	NaN	(none)	NaN	(none)	NaN	(none)	NaN	(none)	wrigh101	Harry Wright	younn801	Nick Young	spala101	Al Spalding	braia102	Asa Brainard	NaN	(none)
4	2	18710506	0	Sat	CL1	na	2	RC1	na	1	12	4	54.0	D	NaN	NaN	NaN	RCK01	1000.0	140.0	610020003	10020100	49.0	11.0	1.0	1.0	0.0	8.0	0.0	0.0	0.0	0.0	-1.0	1.0	0.0	-1.0	-1.0	-1.0	10.0	1.0	0.0	0.0	2.0	0.0	27.0	12.0	8.0	5.0	0.0	0.0	36.0	7.0	2.0	1.0	0.0	2.0	0.0	0.0	0.0	0.0	-1.0	3.0	5.0	-1.0	-1.0	-1.0	5.0	1.0	3.0	3.0	1.0	0.0	27.0	12.0	13.0	3.0	0.0	0.0	mawnj901	J.H. Manny	NaN	(none)	NaN	(none)	NaN	(none)	NaN	(none)	NaN	(none)	paboc101	Charlie Pabor	hasts101	Scott Hastings	prata101	Al Pratt	fishc102	Cherokee Fisher	NaN	(none)
5	3	18710508	0	Mon	CL1	na	3	CH1	na	1	12	14	54.0	D	NaN	NaN	NaN	CHI01	5000.0	150.0	101403111	77000000	46.0	15.0	2.0	1.0	2.0	10.0	0.0	0.0	0.0	0.0	-1.0	1.0	0.0	-1.0	-1.0	-1.0	7.0	1.0	6.0	6.0	0.0	0.0	27.0	15.0	11.0	6.0	0.0	0.0	43.0	11.0	2.0	0.0	0.0	8.0	0.0	0.0	0.0	4.0	-1.0	2.0	1.0	-1.0	-1.0	-1.0	6.0	1.0	4.0	4.0	0.0	0.0	27.0	14.0	7.0	2.0	0.0	0.0	willg901	Gardner Willard	NaN	(none)	NaN	(none)	NaN	(none)	NaN	(none)	NaN	(none)	paboc101	Charlie Pabor	woodj106	Jimmy Wood	zettg101	George Zettlein	prata101	Al Pratt	NaN	(none)
6	4	18710509	0	Tue	BS1	na	2	TRO	na	1	9	5	54.0	D	NaN	NaN	NaN	TRO01	3250.0	145.0	2232	101003000	46.0	17.0	4.0	1.0	0.0	6.0	0.0	0.0	0.0	2.0	-1.0	0.0	1.0	-1.0	-1.0	-1.0	12.0	1.0	2.0	2.0	0.0	0.0	27.0	12.0	5.0	0.0	1.0	0.0	36.0	9.0	0.0	0.0	0.0	2.0	0.0	0.0	0.0	3.0	-1.0	0.0	2.0	-1.0	-1.0	-1.0	7.0	1.0	3.0	3.0	1.0	0.0	27.0	11.0	7.0	3.0	0.0	0.0	leroi901	Isaac Leroy	NaN	(none)	NaN	(none)	NaN	(none)	NaN	(none)	NaN	(none)	wrigh101	Harry Wright	pikel101	Lip Pike	spala101	Al Spalding	mcmuj101	John McMullin	NaN	(none)
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