英文:
Extract only natural numbers belonging to a specific column, for every group/id in Python
问题
# 加载所需的库
import pandas as pd
# 创建数据集
data = {'id': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
2, 2, 2, 2, 2, 2, 2,
3, 3, 3, 3, 3, 3, 3, 3,
4, 4, 4, 4, 4, 4,
5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5],
'cycle': [0.0, 0.2, 0.4, 0.6, 0.8, 1, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2,
0.0, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2,
0.0, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4,
0.0, 0.2, 0.4, 0.6, 0.8, 1.0,
0.0, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0, 3.2],
'Salary': [6, 7, 7, 7, 8, 9, 10, 11, 12, 13, 14, 15,
3, 4, 4, 4, 4, 5, 6,
2, 8, 9, 10, 11, 12, 13, 14,
1, 8, 9, 10, 11, 12,
6, 7, 7, 9, 10, 11, 12, 13, 14, 15, 9, 10, 11, 12, 13, 14, 15],
'Children': ['Yes', 'No', 'Yes', 'Yes', 'Yes', 'Yes', 'No', 'No', 'Yes', 'Yes', 'Yes', 'No',
'Yes', 'Yes', 'Yes', 'No', 'Yes', 'Yes', 'Yes',
'Yes', 'No', 'Yes', 'Yes', 'No', 'No', 'Yes', 'Yes',
'Yes', 'Yes', 'No', 'Yes', 'Yes', 'Yes',
'Yes', 'No', 'Yes', 'No', 'No', 'Yes', 'Yes', 'Yes', 'Yes', 'No', 'No', 'Yes', 'No', 'No', 'Yes', 'Yes', 'Yes'],
'Days': [141, 123, 128, 66, 66, 120, 141, 52, 96, 120, 141, 52,
141, 96, 120, 120, 141, 52, 96,
141, 15, 123, 128, 66, 120, 141, 141,
141, 141, 123, 128, 66, 67,
141, 123, 128, 66, 123, 128, 66, 120, 141, 52, 123, 128, 66, 123, 128, 66, 120]
}
# 转换为数据框
df = pd.DataFrame(data)
print("\n df = \n", df)
以上是你提供的代码部分的翻译。如果你有关于代码的具体问题或需要进一步的解释，请随时提出。
英文:
#Load the required libraries
import pandas as pd
#Create dataset
data = {'id': [1, 1, 1, 1, 1, 1,1, 1, 1, 1, 1, 1,
2, 2, 2, 2, 2, 2, 2,
3, 3, 3, 3, 3, 3, 3,3,
4, 4, 4, 4, 4,4,
5, 5, 5, 5, 5, 5,5, 5, 5,5, 5,5, 5,5, 5, 5,5],
'cycle': [0.0, 0.2,0.4, 0.6, 0.8, 1,1.2,1.4,1.6,1.8,2.0,2.2,
0.0, 0.2,0.4, 0.6,0.8,1.0,1.2,
0.0, 0.2,0.4, 0.6, 0.8,1.0,1.2,1.4,
0.0, 0.2,0.4, 0.6, 0.8,1.0,
0.0, 0.2,0.4, 0.6, 0.8, 1.0,1.2,1.4,1.6,1.8, 2.0,2.2,2.4,2.6,2.8,3.0,3.2],
'Salary': [6, 7, 7, 7,8,9,10,11,12,13,14,15,
3, 4, 4, 4,4,5,6,
2, 8,9,10,11,12,13,14,
1, 8,9,10,11,12,
6, 7, 7,9,10,11,12,13,14,15, 9,10,11,12,13,14,15],
'Children': ['Yes', 'No', 'Yes', 'Yes', 'Yes', 'Yes', 'No','No', 'Yes', 'Yes', 'Yes', 'No',
'Yes', 'Yes', 'Yes', 'No', 'Yes', 'Yes', 'Yes',
'Yes', 'No','Yes', 'Yes', 'No','No', 'Yes','Yes',
'Yes', 'Yes', 'No','Yes', 'Yes','Yes',
'Yes', 'No', 'Yes', 'No', 'No', 'Yes', 'Yes', 'Yes', 'Yes', 'No', 'No', 'Yes', 'No', 'No', 'Yes', 'Yes', 'Yes'],
'Days': [141, 123, 128, 66, 66, 120, 141, 52,96, 120, 141, 52,
141, 96, 120,120, 141, 52,96,
141, 15,123, 128, 66, 120, 141, 141,
141, 141,123, 128, 66,67,
141, 123, 128, 66, 123, 128, 66, 120, 141, 52, 123, 128, 66, 123, 128, 66, 120,],
}
#Convert to dataframe
df = pd.DataFrame(data)
print("\n df = \n",df)
The above dataset looks as such:
Here for every 'id', I wish to extract only those rows, whose 'cycle' is an natural number, as shown in the boxes of the above image file.
The expected dataframe is as such:
Can somebody please let me know how to achieve this task in Pyhton?
答案1
得分: 1
筛选出不等于0的值，并比较整数值是否与浮点数值相同：
out = df[df['cycle'].ne(0) & df['cycle'].astype(int).eq(df['cycle'])].reset_index(drop=True)
print(out)
id cycle Salary Children Days
0 1 1.0 9 Yes 120
1 2 1.0 5 Yes 52
2 3 1.0 12 No 120
3 4 1.0 12 Yes 67
4 5 1.0 11 Yes 128
5 5 2.0 9 No 123
6 5 3.0 14 Yes 66
英文:
Filter out 0 values and compare if integer values is same like float value:
out=df[df['cycle'].ne(0) & df['cycle'].astype(int).eq(df['cycle'])].reset_index(drop=True)
print (out)
id cycle Salary Children Days
0 1 1.0 9 Yes 120
1 1 2.0 14 Yes 141
2 2 1.0 5 Yes 52
3 3 1.0 12 No 120
4 4 1.0 12 Yes 67
5 5 1.0 11 Yes 128
6 5 2.0 9 No 123
7 5 3.0 14 Yes 66
答案2
得分: 1
这是另一种方法：
df[(df['cycle']!=0.0) & (df['cycle']%0.5==0)].reset_index()
英文:
Here's another way:
df[(df['cycle']!=0.0) & (df['cycle']%0.5==0)].reset_index()
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