“ \”换行符使pandas dataframe列按字母顺序重新排序

时间:2018-10-04 14:32:30

标签: python pandas

我的代码太大了,所以我开始使用“ \”以提高可读性。但是我注意到,这样做可以使我的列按字母顺序重新排序。

有人知道如何阻止这种情况的发生吗?

代码如下:

def unsettled_event(team_name,market):
    """Returns all bets tied to this specific event."""
    combos_list = df[(df["home"] == team_name) \
                     & (df["profit"].isnull()) \
                     & (df["market"] == market) \
                     & (df['settled_date']).isnull()].combo_id.dropna().unique()
    df_combos = df[df["combo_id"].isin(combos_list)].sort_values("combo_id") \
                [["combo_id", "home", "market", "odds", "selection", "bookmaker", "broker", "stake_adj", "is_won"]] 
    df_singles = df[(df["home"] == team_name) \
                    & (df["leg_size"] == 1) \
                    & (df["profit"].isnull()) \
                    & (df["market"] == market) \
                    & (df['settled_date']).isnull()] \
                [["combo_id", "home", "market", "selection", "odds", "bookmaker", "broker", "stake_adj", "is_won"]]
    return pd.concat([df_singles, df_combos], ignore_index=True)

所以最后,df.columns返回了:

['bookmaker', 'broker', 'combo_id', 'home', 'is_won', 'market', 'odds', 'selection', 'stake_adj']

它应该返回:

["combo_id", "home", "market", "selection", "odds", "bookmaker", "broker", "stake_adj", "is_won"]

1 个答案:

答案 0 :(得分:1)

如果要以特定顺序显示相关列,请在输出中指定它们:

df[["combo_id", "home", "market", "selection", "odds", "bookmaker", 
    "broker", "stake_adj", "is_won"]].head()

内幕下,顺序无关紧要。如果它在输出中很重要,那么最好将其明确化。

(请注意,超过一半的时间,结果在输出中也无关紧要。)


您也不需要反斜杠。

例如,这很好,并且具有更多的Python风格:

def unsettled_event(team_name,market):
    """Returns all bets tied to this specific event."""
    columns = ["combo_id", "home", "market", "selection", "odds",
               "bookmaker", "broker", "stake_adj", "is_won"]
    combos_list = df[(df["home"] == team_name)
                     & (df["profit"].isnull())
                     & (df["market"] == market)
                     & (df['settled_date']).isnull()].combo_id.dropna().unique()
    df_combos = df[df["combo_id"].isin(combos_list)].sort_values("combo_id")[columns]     
    df_singles = df[(df["home"] == team_name)
                    & (df["leg_size"] == 1)
                    & (df["profit"].isnull())
                    & (df["market"] == market)
                    & (df['settled_date']).isnull()][columns]
    return pd.concat([df_singles, df_combos], ignore_index=True)

您可能还需要进行一些其他更改,删除一些多余的部分,但这只是要点。尽管[...]之间保持了换行符,但它们仍将保持在一起。