在熊猫上进行循环

Question

让我们假设我有一个带有“日期”列的df用来过滤我想要的冠军，并且我通过将“日期”列设置为索引来做到这一点。而且，我有一个功能可以根据需要配置所有列类型：

import pandas as pd
df = pd.DataFrame({'Date':['26-12-2018','26-12-2018','27-12-2018','27-12-2018','28-12-2018','28-12-2018'],
                   'In':['A','B','D','Z','Q','E'],
                   'Out' : ['Z', 'D', 'F', 'H', 'Z', 'A'],
                   'Score_in' : ['6', '2', '1', '0', '1', '3'], 
                   'Score_out' : ['2','3','0', '1','1','3'],
                   'Place' : ['One','Two','Four', 'Two','Two','One']})

例如，我可以在同一图上绘制它吗（因为它是网格）

df.groupby('In').Score_in.sum().add(df.groupby('Out').Score_out.sum())

通过传递函数参数“ day”作为迭代器，每天使用for循环？ 我不知道效果如何，

for it in range(26:28:1):

    if it == day:
        ..plot_settings.. f(it)

Answer 1

这是一段代码，用于建立数据的matplotlib图。应该注意的是，据我所知，matplotlib并不是这种绘图的最友好软件包。

import matplotlib.pyplot as plt 
import matplotlib.dates as mdates 

df["score"] = pd.to_numeric(df["score"])
df = df.groupby(["Date", "team"]).sum()
df = df.reset_index()

fig, ax = plt.subplots()

groups = df.Date.unique()
num_groups = len(groups)

ind = np.arange(num_groups)    # the x locations for the groups
width = 0.10                   # the width of the bars

days = pd.date_range(df.Date.min(), df.Date.max(), freq = "1D")

rect_list = []
for inx, t in enumerate(df.team.unique()) :
    sub_df = df[df.team == t]
    sub_df = sub_df.set_index("Date").reindex(days)

    x_locations = ind + width * inx
    rects = ax.bar(x_locations, sub_df.score, width, bottom = 0)
    rect_list.append(rects)

ax.legend(rect_list, df.team.unique())
        
ax.set_xticks(ind + width*2)

labels = [pd.to_datetime(x).strftime("%Y-%m-%d") for x in groups]
ax.set_xticklabels(labels)

fig.show()

结果是：

如果您希望将每一天都放在一个单独的图中，则可以执行以下操作：

import matplotlib.pyplot as plt 
import matplotlib.dates as mdates 

df["score"] = pd.to_numeric(df["score"])
df = df.groupby(["Date", "team"]).sum()
df = df.reset_index()

days = df.Date.unique()

fig, subplots = plt.subplots(len(days), 1)

all_teams = df.team.unique()

for d, ax in zip(days, subplots):

    sub_df = df[df.Date == d]
    
    sub_df.set_index("team", inplace=True)
    sub_df = sub_df.reindex(all_teams).sort_index().fillna(value = 0)
    
    rects = ax.bar(sub_df.index, sub_df.score, width, bottom = 0)
    ax.set_title(pd.to_datetime(d).strftime("%Y-%m-%d"))

plt.show()

输出：