我有一個如下所示的數(shù)據(jù)框。首先，我想要每個日期中每個狀態(tài)的計(jì)數(shù)。例如，2017-11-02 中“完成”的數(shù)量是 2。我想要這樣的堆棧圖。 status start_time end_time \0 COMPLETED 2017-11-01 19:58:54.726 2017-11-01 20:01:05.414 1 COMPLETED 2017-11-02 19:43:04.000 2017-11-02 19:47:54.877 2 ABANDONED_BY_USER 2017-11-03 23:36:19.059 2017-11-03 23:36:41.045 3 ABANDONED_BY_TIMEOUT 2017-10-31 17:02:38.689 2017-10-31 17:12:38.844 4 COMPLETED 2017-11-02 19:35:33.192 2017-11-02 19:42:51.074 這是數(shù)據(jù)框的csv：status,start_time,end_timeCOMPLETED,2017-11-01 19:58:54.726,2017-11-01 20:01:05.414COMPLETED,2017-11-02 19:43:04.000,2017-11-02 19:47:54.877ABANDONED_BY_USER,2017-11-03 23:36:19.059,2017-11-03 23:36:41.045ABANDONED_BY_TIMEOUT,2017-10-31 17:02:38.689,2017-10-31 17:12:38.844COMPLETED,2017-11-02 19:35:33.192,2017-11-02 19:42:51.074ABANDONED_BY_TIMEOUT,2017-11-02 19:35:33.192,2017-11-02 19:42:51.074為達(dá)到這個：df_['status'].astype('category')df_ = df_.set_index('start_time')grouped = df_.groupby('status')color = {'COMPLETED':'green','ABANDONED_BY_TIMEOUT':'blue',"MISSED":'red',"ABANDONED_BY_USER":'yellow'}for key_, group in grouped: print(key_) df_ = group.groupby(lambda x: x.date).count() print(df_) df_['status'].plot(label=key_,kind='bar',stacked=True,\ color=color[key_],rot=90)plt.show()以下輸出是：ABANDONED_BY_TIMEOUT status end_time 2017-10-31 1 1 ABANDONED_BY_USER status end_time 2017-11-03 1 1 COMPLETED status end_time 2017-11-01 1 1 2017-11-02 2 2 正如我們所看到的，這里的問題只考慮了最后兩個日期“2017-11-01”和“2017-11-02”，而不是所有類別中的所有日期。我該如何解決這個問題？歡迎使用全新的堆疊圖方法。提前致謝。
3 回答
慕桂英3389331
TA貢獻(xiàn)2036條經(jīng)驗(yàn) 獲得超8個贊
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df_ = pd.read_csv('sam.csv')
df_['date'] = pd.to_datetime(df_['start_time']).dt.date
df_ = df_.set_index('start_time')
grouped = pd.DataFrame(df_.groupby(['date', 'status']).size().reset_index(name="count")).pivot(columns='status', index='date', values='count')
print(grouped)
sns.set()
grouped.plot(kind='bar', stacked=True)
# g = grouped.plot(x='date', kind='bar', stacked=True)
plt.show()
輸出：
慕森卡
TA貢獻(xiàn)1806條經(jīng)驗(yàn) 獲得超8個贊
嘗試轉(zhuǎn)型df_與pandas.crosstab替代：
color = ['blue', 'yellow', 'green', 'red']
df_xtab = pd.crosstab(df_.start_time.dt.date, df_.status)
這DataFrame看起來像：
status ABANDONED_BY_TIMEOUT ABANDONED_BY_USER COMPLETED
start_time
2017-10-31 1 0 0
2017-11-01 0 0 1
2017-11-02 1 0 2
2017-11-03 0 1 0
并且更容易繪制。
df_xtab.plot(kind='bar',stacked=True, color=color, rot=90)
夢里花落0921
TA貢獻(xiàn)1772條經(jīng)驗(yàn) 獲得超6個贊
使用barplot帶有色調(diào)的seaborn 庫
代碼：
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df_ = pd.read_csv('sam.csv')
df_['date'] = pd.to_datetime(df_['start_time']).dt.date
df_ = df_.set_index('start_time')
print(df_)
grouped = pd.DataFrame(df_.groupby(['date', 'status']).size().reset_index(name="count"))
print(grouped)
g = sns.barplot(x='date', y='count', hue='status', data=grouped)
plt.show()
輸出：
數(shù)據(jù)：
status,start_time,end_time
COMPLETED,2017-11-01 19:58:54.726,2017-11-01 20:01:05.414
COMPLETED,2017-11-02 19:43:04.000,2017-11-02 19:47:54.877
ABANDONED_BY_USER,2017-11-03 23:36:19.059,2017-11-03 23:36:41.045
ABANDONED_BY_TIMEOUT,2017-10-31 17:02:38.689,2017-10-31 17:12:38.844
COMPLETED,2017-11-02 19:35:33.192,2017-11-02 19:42:51.074
ABANDONED_BY_TIMEOUT,2017-11-02 19:35:33.192,2017-11-02 19:42:51.074
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