熊猫-在df中计数行以发现每天的生存率

时间:2019-01-31 06:20:20

标签: python pandas pandas-groupby sklearn-pandas

你好,伙计们!

我有一个dfA(表A),其中包含某些产品的可用天数(days_survived)。我需要计算每天总共可用的产品数量(表B)。我的意思是,我需要对dfA中的行进行计数,以发现头5天(df2)每天的生存率。

表A:

+-------+--------------+
| id    | days_survived|
+-------+--------------+
| 1     |  1           |
| 2     |  3           |
| 3     |  10          | 
| 4     |  40          |
| 5     |  4           |
| 6     |  9           |
+-------+--------------+

表B(分析前5天的预期结果):

+-------+----------------+
| day   | #count_survived|
+-------+----------------+
| 1     |  6             |
| 2     |  5             |
| 3     |  5             | 
| 4     |  4             |
| 5     |  3             |
+-------+----------------+

此结果意味着在第一天总共提供了6种产品,然后在第二天和第三天只有5种产品,然后在第四天只有4种产品,最后在第五天只有3种产品。

代码:

# create df
import pandas as pd
d = {'id': [1,2,3,4,5,6], 'days_survived': [1,3,10,40,4,9]}
dfA = pd.DataFrame(data=d) 

有人可以帮助我吗? :)

2 个答案:

答案 0 :(得分:2)

将列表理解与展平和过滤一起使用,然后计数:

comp = [y for x in dfA['days_survived'] for y in range(1, x + 1) if y < 6]
s = pd.Series(comp).value_counts().rename_axis('day').reset_index(name='#count_survived')
print (s)
   day  #count_survived
0    1                6
1    3                5
2    2                5
3    4                4
4    5                3

使用Counter的另一种解决方案:

from collections import Counter

comp = [y for x in dfA['days_survived'] for y in range(1, x + 1) if y < 6]
d = Counter(comp)
df = pd.DataFrame({'day':list(d.keys()), '#count_survived':list(d.values())})

答案 1 :(得分:0)

这是在使用“收藏夹”,它创建了一个项目存在的所有天数的列表,然后从列表中计算每天发生的次数

import pandas as pd
import numpy as np
from collections import Counter

df = pd.DataFrame(data={'id': [1,2,3,4,5,6], 'days_survived': [1,3,10,40,4,9]})
# We will create a new column having values as a list of all the days for which item was present
df['Days'] = df.apply(lambda a :  list(np.arange(1,a.days_survived+1)),axis=1)
# Applyin Counter to the flattened list of all elements in 'Days' column
cnt= Counter([item for items in list(df['Days']) for item in items])
#Converting cnt Counter object to Dataframe
df_new = pd.DataFrame(data= {'Days':list(cnt.keys()),'count':list(cnt.values())})

希望这会有所帮助。