我正在嘗試將嵌套的 dicts 提取到我的資料框中，資料當前存盤在資料框中的一列中，并且努力將屬性作為列標題提取到行中。我嘗試將其進一步分解為資料中的統計資料，但出現錯誤。有人可以幫忙嗎？
text_last5610 = responseteamlast5610.content
tree_last5610 = json.loads(text_last5610)
d_last5610 = tree_last5610["data"]
df_last5610 = pd.DataFrame(d_last5610)
df_last5610.head()
在此輸入圖片說明 在此
輸入圖片說明
{
"data": [
{
"alt_names": [
"The Clarets"
],
"competition_id": -1,
"continent": null,
"country": "England",
"english_name": "Burnley FC",
"founded": "1882",
"full_name": "Burnley FC",
"id": 145,
"image": "https://cdn.footystats.org/img/teams/england-burnley-fc.png",
"last_updated_match_timestamp": 1639317600,
"last_x_home_away_or_overall": "0",
"last_x_match_num": 5,
"name": "Burnley",
"official_sites": [
"https://www.burnleyfootballclub.com/"
],
"performance_rank": 0,
"risk": 60,
"season": "2021",
"season_format": "Domestic League",
"stats": {
"AVGHT_away": 0.67,
"AVGHT_home": 2.5,
"AVGHT_overall": 1.4,
"AVG_2hg_away": 0.33,
"AVG_2hg_home": 0.5,
"AVG_2hg_overall": 0.4,
"BTTS_and_draw_away": 1,
"BTTS_and_draw_home": 1,
"BTTS_and_draw_overall": 2,
"BTTS_and_draw_percentage_away": 33,
"BTTS_and_draw_percentage_home": 50,
"BTTS_and_draw_percentage_overall": 40,
"BTTS_and_lose_away": 0,
"BTTS_and_lose_home": 0,
"BTTS_and_lose_overall": 0,
"BTTS_and_lose_percentage_away": 0,
"BTTS_and_lose_percentage_home": 0,
"BTTS_and_lose_percentage_overall": 0,
"BTTS_and_win_away": 0,
"BTTS_and_win_home": 0,
"BTTS_and_win_overall": 0,
"BTTS_and_win_percentage_away": 0,
"BTTS_and_win_percentage_home": 0,
"BTTS_and_win_percentage_overall": 0,
"BTTS_both_halves_away": 0,
"BTTS_both_halves_home": 0,
"BTTS_both_halves_overall": 0,
"BTTS_both_halves_percentage_away": 0,
"BTTS_both_halves_percentage_home": 0,
"BTTS_both_halves_percentage_overall": 0,
"GoalDifferenceHT_away": -2,
"GoalDifferenceHT_home": -1,
"GoalDifferenceHT_overall": -3,
"GoalsHT_away": 2,
"GoalsHT_home": 5,
"GoalsHT_overall": 7,
"HTPPG_away": 0.33,
"HTPPG_home": 0.5,
"HTPPG_overall": 0.4,
"HTPoints_away": 1,
"HTPoints_home": 1,
"HTPoints_overall": 2,
"additional_info": {
"2h_cards_against_avg_away": 1,
"2h_cards_against_avg_home": 1.5,
"2h_cards_against_avg_overall": 1.2,
"2h_cards_against_away": 3,
"2h_cards_against_home": 3,
"2h_cards_against_overall": 6,
"2h_cards_for_avg_away": 2,
"2h_cards_for_avg_home": 0.5,
"2h_cards_for_avg_overall": 1.4,
"2h_cards_for_away": 6,
"2h_cards_for_home": 1,
"2h_cards_for_over05_percentage_away": 100,
"2h_cards_for_over05_percentage_home": 50,
"2h_cards_for_over05_percentage_overall": 80,
"2h_cards_for_overall": 7,
"2h_cards_total_avg_away": 3,
"2h_cards_total_avg_home": 2,
"2h_cards_total_avg_overall": 2.6,
"2h_cards_total_away": 9,
"2h_cards_total_home": 4,
"2h_cards_total_overall": 13,
"2h_half_with_most_cards_total_percentage_away": 67,
"2h_half_with_most_cards_total_percentage_home": 50,
"2h_half_with_most_cards_total_percentage_overall": 60,
"2h_total_cards_2to3_percentage_away": 67,
"2h_total_cards_2to3_percentage_home": 50,
"2h_total_cards_2to3_percentage_overall": 60,
"2h_total_cards_over3_percentage_away": 33,
"2h_total_cards_over3_percentage_home": 0,
"2h_total_cards_over3_percentage_overall": 20,
"2h_total_cards_under2_percentage_away": 0,
"2h_total_cards_under2_percentage_home": 50,
"2h_total_cards_under2_percentage_overall": 20,
"attack_num_recoded_matches_away": 3,
"attack_num_recoded_matches_home": 1,
"attacks_num_away": 302,
"attacks_num_home": 103,
"btts_1h2h_no_no_num_away": 3,
"btts_1h2h_no_no_num_home": 1,
"btts_1h2h_no_no_num_overall": 4,
"btts_1h2h_no_no_percentage_away": 100,
"btts_1h2h_no_no_percentage_home": 50,
"btts_1h2h_no_no_percentage_overall": 80,
"btts_1h2h_no_yes_num_away": 0,
"btts_1h2h_no_yes_num_home": 0,
"btts_1h2h_no_yes_num_overall": 0,
"btts_1h2h_no_yes_percentage_away": 0,
"btts_1h2h_no_yes_percentage_home": 0,
"btts_1h2h_no_yes_percentage_overall": 0,
"btts_1h2h_yes_no_num_away": 0,
"btts_1h2h_yes_no_num_home": 1,
"btts_1h2h_yes_no_num_overall": 1,
"btts_1h2h_yes_no_percentage_away": 0,
"btts_1h2h_yes_no_percentage_home": 50,
"btts_1h2h_yes_no_percentage_overall": 20,
"btts_1h2h_yes_yes_num_away": 0,
"btts_1h2h_yes_yes_num_home": 0,
"btts_1h2h_yes_yes_num_overall": 0,
"btts_1h2h_yes_yes_percentage_away": 0,
"btts_1h2h_yes_yes_percentage_home": 0,
"btts_1h2h_yes_yes_percentage_overall": 0,
"cardTimingRecorded_matches_away": 3,
"cardTimingRecorded_matches_home": 2,
"cardTimingRecorded_matches_overall": 5,
"cardsRecorded_matches_away": 3,
"cardsRecorded_matches_home": 2,
"cardsRecorded_matches_overall": 5,
"cards_against_avg_away": 1.33,
"cards_against_avg_home": 2,
"cards_against_avg_overall": 1.6,
"cards_against_away": 4,
"cards_against_home": 4,
"cards_against_overall": 8,
"cards_for_avg_away": 2.67,
"cards_for_avg_home": 2,
"cards_for_avg_overall": 2.4,
"cards_for_away": 8,
"cards_for_home": 4,
"cards_for_overall": 12,
"cards_total_avg_away": 4,
"cards_total_avg_home": 4,
"cards_total_avg_overall": 4,
"cards_total_away": 12,
"cards_total_home": 8,
"cards_total_overall": 20,
"corners_earned_1h_2_to_3_num_away": 1,
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"corners_earned_1h_2_to_3_percentage_away": 33,
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"corners_earned_1h_avg_away": 1.67,
"corners_earned_1h_avg_home": 1,
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"corners_earned_1h_num_away": 5,
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"corners_earned_1h_over2_num_away": 1,
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"corners_earned_1h_over2_percentage_away": 33,
"corners_earned_1h_over2_percentage_home": 0,
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"corners_earned_1h_over3_num_away": 0,
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"corners_earned_1h_over3_percentage_away": 0,
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"corners_earned_1h_over3_percentage_overall": 0,
"corners_earned_2h_2_to_3_num_away": 2,
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"corners_earned_2h_2_to_3_percentage_away": 67,
"corners_earned_2h_2_to_3_percentage_home": 100,
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"corners_earned_2h_avg_away": 1.67,
"corners_earned_2h_avg_home": 2,
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"corners_earned_2h_num_away": 5,
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"corners_earned_2h_over2_num_away": 0,
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"corners_earned_2h_over2_percentage_away": 0,
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"corners_earned_2h_over3_num_away": 0,
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"corners_earned_2h_over3_percentage_away": 0,
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"corners_earned_2h_over3_percentage_overall": 0,
"dangerous_attacks_num_away": 108,
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"draw_0_10_num_away": 3,
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"draw_0_10_percentage_away": 100,
"draw_0_10_percentage_home": 50,
"draw_0_10_percentage_overall": 80,
"exact_team_goals_0_ft_away": 2,
"exact_team_goals_0_ft_overall": 3,
"exact_team_goals_0_ft_percentage_away": 67,
"exact_team_goals_0_ft_percentage_home": 50,
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"exact_team_goals_1_ft_away": 1,
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"exact_team_goals_1_ft_percentage_away": 33,
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"exact_team_goals_2_ft_away": 0,
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"exact_team_goals_2_ft_percentage_away": 0,
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"exact_team_goals_3_ft_away": 0,
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"exact_total_goals_0_ft_away": 1,
"exact_total_goals_0_ft_home": 1,
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"exact_total_goals_1_ft_away": 1,
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"exact_total_goals_2_ft_away": 1,
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"exact_total_goals_3_ft_away": 0,
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"exact_total_goals_4_ft_away": 0,
"exact_total_goals_4_ft_home": 0,
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"exact_total_goals_5_ft_away": 0,
"exact_total_goals_5_ft_home": 0,
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"exact_total_goals_6_ft_away": 0,
"exact_total_goals_6_ft_home": 1,
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"exact_total_goals_7_ft_away": 0,
"exact_total_goals_7_ft_home": 0,
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"fh_cards_against_avg_away": 0.33,
"fh_cards_against_avg_home": 0.5,
"fh_cards_against_avg_overall": 0.4,
"fh_cards_against_away": 1,
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"fh_cards_for_avg_away": 0.67,
"fh_cards_for_avg_home": 1.5,
"fh_cards_for_avg_overall": 1,
"fh_cards_for_away": 2,
"fh_cards_for_home": 3,
"fh_cards_for_over05_percentage_away": 33,
"fh_cards_for_over05_percentage_home": 100,
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"fh_cards_for_overall": 5,
"fh_cards_total_avg_away": 1,
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"fh_cards_total_away": 3,
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"fh_half_with_most_cards_total_percentage_away": 33,
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"fh_half_with_most_cards_total_percentage_overall": 40,
"fh_total_cards_2to3_percentage_away": 33,
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"fh_total_cards_over3_percentage_away": 0,
"fh_total_cards_over3_percentage_home": 0,
"fh_total_cards_over3_percentage_overall": 0,
"fh_total_cards_under2_percentage_away": 67,
"fh_total_cards_under2_percentage_home": 0,
"fh_total_cards_under2_percentage_overall": 40,
"formRun_away": "ddl",
"formRun_home": "dd",
"formRun_overall": "dddld",
"fouls_against_avg_away": 6.67,
"fouls_against_avg_home": 15,
"fouls_against_avg_overall": 8.75,
"fouls_against_num_away": 20,
"fouls_against_num_home": 15,
"fouls_against_num_overall": 35,
"fouls_recorded_away": 3,
"fouls_recorded_home": 1,
"fouls_recorded_overall": 4,
"freekicks_recorded_matches_away": 0,
"freekicks_recorded_matches_home": 0,
"freekicks_recorded_matches_overall": 0,
"freekicks_team_avg_away": 0,
"freekicks_team_avg_home": 0,
"freekicks_team_avg_overall": 0,
"freekicks_team_num_away": 0,
"freekicks_team_num_home": 0,
"freekicks_team_num_overall": 0,
"freekicks_team_over105_away": 0,
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"freekicks_team_over115_away": 0,
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"freekicks_team_over125_away": 0,
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"freekicks_team_over135_away": 0,
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"freekicks_team_over145_away": 0,
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"freekicks_team_over165_away": 0,
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"freekicks_team_over175_away": 0,
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"freekicks_team_over75_away": 0,
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"freekicks_team_over85_away": 0,
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"freekicks_team_over95_away": 0,
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"freekicks_team_over95_overall": 0,
"freekicks_total_avg_away": 0,
"freekicks_total_avg_home": 0,
"freekicks_total_avg_overall": 0,
"freekicks_total_num_away": 0,
"freekicks_total_num_home": 0,
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"freekicks_total_over205_away": 0,
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"freekicks_total_over215_away": 0,
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"freekicks_total_over225_away": 0,
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"freekicks_total_over235_away": 0,
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"freekicks_total_over245_away": 0,
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"freekicks_total_over255_away": 0,
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"freekicks_total_over265_away": 0,
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"freekicks_total_over275_away": 0,
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"freekicks_total_over285_away": 0,
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"freekicks_total_over295_away": 0,
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"freekicks_total_over305_away": 0,
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"freekicks_total_over305_overall": 0,
"goal_kicks_recorded_matches_away": 0,
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"goal_kicks_recorded_matches_overall": 0,
"goal_kicks_team_avg_away": 0,
"goal_kicks_team_avg_home": 0,
"goal_kicks_team_avg_overall": 0,
"goal_kicks_team_num_away": 0,
"goal_kicks_team_num_home": 0,
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"goal_kicks_team_over105_away": 0,
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"goal_kicks_team_over115_away": 0,
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"goal_kicks_team_over115_overall": 0,
"goal_kicks_team_over35_away": 0,
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"goal_kicks_team_over35_overall": 0,
"goal_kicks_team_over45_away": 0,
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"goal_kicks_team_over45_overall": 0,
"goal_kicks_team_over55_away": 0,
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"goal_kicks_team_over65_away": 0,
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"goal_kicks_team_over65_overall": 0,
"goal_kicks_team_over75_away": 0,
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"goal_kicks_team_over85_away": 0,
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"goal_kicks_team_over95_away": 0,
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"goal_kicks_total_avg_away": 0,
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"goal_kicks_total_num_away": 0,
"goal_kicks_total_num_home": 0,
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"goal_kicks_total_over105_away": 0,
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"goal_kicks_total_over115_away": 0,
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"goal_kicks_total_over115_overall": 0,
"goal_kicks_total_over125_away": 0,
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"goal_kicks_total_over125_overall": 0,
"goal_kicks_total_over135_away": 0,
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"goal_kicks_total_over145_away": 0,
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"goal_kicks_total_over155_away": 0,
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"goal_kicks_total_over165_away": 0,
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"goal_kicks_total_over175_away": 0,
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"goal_kicks_total_over185_away": 0,
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"goal_kicks_total_over185_overall": 0,
"goal_kicks_total_over85_away": 0,
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"goal_kicks_total_over95_away": 0,
"goal_kicks_total_over95_home": 0,
"goal_kicks_total_over95_overall": 0,
"half_with_most_corners_is_1h_num_away": 1,
"half_with_most_corners_is_1h_num_home": 0,
"half_with_most_corners_is_1h_num_overall": 1,
"half_with_most_corners_is_1h_percentage_away": 33,
"half_with_most_corners_is_1h_percentage_home": 0,
"half_with_most_corners_is_1h_percentage_overall": 25,
"half_with_most_corners_is_2h_num_away": 1,
"half_with_most_corners_is_2h_num_home": 1,
"half_with_most_corners_is_2h_num_overall": 2,
"half_with_most_corners_is_2h_percentage_away": 33,
"half_with_most_corners_is_2h_percentage_home": 100,
"half_with_most_corners_is_2h_percentage_overall": 50,
"half_with_most_corners_is_draw_num_away": 1,
"half_with_most_corners_is_draw_num_home": 0,
"half_with_most_corners_is_draw_num_overall": 1,
"half_with_most_corners_is_draw_percentage_away": 33,
"half_with_most_corners_is_draw_percentage_home": 0,
"half_with_most_corners_is_draw_percentage_overall": 25,
"half_with_most_goals_is_1h_num_away": 1,
"half_with_most_goals_is_1h_num_home": 1,
"half_with_most_goals_is_1h_num_overall": 2,
"half_with_most_goals_is_1h_percentage_away": 33,
"half_with_most_goals_is_1h_percentage_home": 50,
"half_with_most_goals_is_1h_percentage_overall": 40,
"half_with_most_goals_is_2h_num_away": 0,
"half_with_most_goals_is_2h_num_home": 0,
"half_with_most_goals_is_2h_num_overall": 0,
uj5u.com熱心網友回復：
類似的問題在 Stackoverflow 上出現過幾次。
您可以使用 .apply(pd.Series)
stats = df['stats'].apply(pd.Series)
將列中的字典轉換stats為DataFrame具有分隔列中所有值的新字典。
稍后你可以使用 .join()
df = df.join(stats)
將這些列從新追加DataFrame到原始DataFrame
我也曾經從原始del列中洗掉列statsDataFrame
每個人都可以簡單地復制和運行的最小作業示例。
json = {
"data": [
{
"id": 145,
"stats": {
"AVGHT_away": 0.67,
"AVGHT_home": 2.5,
"AVGHT_overall": 1.4,
}
},
{
"id": 146,
"stats": {
"AVGHT_away": 1.67,
"AVGHT_home": 0.5,
"AVGHT_overall": 3.4,
}
}
]
}
import pandas as pd
df = pd.DataFrame(json["data"])
print('--- before ---')
print(df)
stats = df['stats'].apply(pd.Series)
print('--- stats ---')
print(stats)
df = df.join(stats)
del df['stats']
print('--- after ---')
print(df)
結果：
--- before ---
id stats
0 145 {'AVGHT_away': 0.67, 'AVGHT_home': 2.5, 'AVGHT...
1 146 {'AVGHT_away': 1.67, 'AVGHT_home': 0.5, 'AVGHT...
--- stats ---
AVGHT_away AVGHT_home AVGHT_overall
0 0.67 2.5 1.4
1 1.67 0.5 3.4
--- after ---
id AVGHT_away AVGHT_home AVGHT_overall
0 145 0.67 2.5 1.4
1 146 1.67 0.5 3.4
編輯：
似乎 sictionarystats也嵌套了字典，additional_info因此您必須為additional_info.
json = {
"data": [
{
"id": 145,
"stats": {
"AVGHT_away": 0.67,
"AVGHT_home": 2.5,
"additional_info": {
"2h_cards_against_avg_away": 1,
"2h_cards_against_avg_home": 1.5,
}
}
},
{
"id": 146,
"stats": {
"AVGHT_away": 1.67,
"AVGHT_home": 0.5,
"additional_info": {
"2h_cards_against_avg_away": 1,
"2h_cards_against_avg_home": 1.5,
}
}
}
]
}
import pandas as pd
df = pd.DataFrame(json["data"])
print('--- before ---')
print(df.to_string())
# ---
stats = df['stats'].apply(pd.Series)
print('--- stats ---')
print(stats.to_string())
# ---
df = df.join(stats)
del df['stats']
print('--- after ---')
print(df.to_string())
# ---
additional_info = df['additional_info'].apply(pd.Series)
print('--- additional_info ---')
print(additional_info)
# ---
df = df.join(additional_info)
del df['additional_info']
print('--- after ---')
print(df.to_string())
結果：
--- before ---
id stats
0 145 {'AVGHT_away': 0.67, 'AVGHT_home': 2.5, 'additional_info': {'2h_cards_against_avg_away': 1, '2h_cards_against_avg_home': 1.5}}
1 146 {'AVGHT_away': 1.67, 'AVGHT_home': 0.5, 'additional_info': {'2h_cards_against_avg_away': 1, '2h_cards_against_avg_home': 1.5}}
--- stats ---
AVGHT_away AVGHT_home additional_info
0 0.67 2.5 {'2h_cards_against_avg_away': 1, '2h_cards_against_avg_home': 1.5}
1 1.67 0.5 {'2h_cards_against_avg_away': 1, '2h_cards_against_avg_home': 1.5}
--- after ---
id AVGHT_away AVGHT_home additional_info
0 145 0.67 2.5 {'2h_cards_against_avg_away': 1, '2h_cards_against_avg_home': 1.5}
1 146 1.67 0.5 {'2h_cards_against_avg_away': 1, '2h_cards_against_avg_home': 1.5}
--- additional_info ---
2h_cards_against_avg_away 2h_cards_against_avg_home
0 1.0 1.5
1 1.0 1.5
--- after ---
id AVGHT_away AVGHT_home 2h_cards_against_avg_away 2h_cards_against_avg_home
0 145 0.67 2.5 1.0 1.5
1 146 1.67 0.5 1.0 1.5
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