如何将多个单元格中的字符串聚合到一个单元格中?
How can I aggregate strings from many cells into one cell?
假设我有两个 class,每个 class 都有几个学生,我想考虑每个 class 中可能的配对。在我的原始数据中,每个学生一行。
Pandas 中转换此数据集的最简单方法是什么
Class Students
0 1 A
1 1 B
2 1 C
3 1 D
4 1 E
5 2 F
6 2 G
7 2 H
喜欢这个新东西吗?
Class Students
0 1 A,B
1 1 A,C
2 1 A,D
3 1 A,E
4 1 B,C
5 1 B,D
6 1 B,E
7 1 C,D
6 1 B,E
8 1 C,D
9 1 C,E
10 1 D,E
11 2 F,G
12 2 F,H
12 2 G,H
试试这个:
import itertools
import pandas as pd
cla = [1, 1, 1, 1, 1, 2, 2, 2]
s = ["A", "B", "C", "D" , "E", "F", "G", "H"]
df = pd.DataFrame(cla, columns=["Class"])
df['Student'] = s
def create_combos(list_students):
combos = itertools.combinations(list_students, 2)
str_students = []
for i in combos:
str_students.append(str(i[0])+","+str(i[1]))
return str_students
def iterate_df(class_id):
df_temp = df.loc[df['Class'] == class_id]
list_student = list(df_temp['Student'])
list_combos = create_combos(list_student)
list_id = [class_id for i in list_combos]
return list_id, list_combos
list_classes = set(list(df['Class']))
new_id = []
new_combos = []
for idx in list_classes:
tmp_id, tmp_combo = iterate_df(idx)
new_id += tmp_id
new_combos += tmp_combo
new_df = pd.DataFrame(new_id, columns=["Class"])
new_df["Student"] = new_combos
print(new_df)
假设我有两个 class,每个 class 都有几个学生,我想考虑每个 class 中可能的配对。在我的原始数据中,每个学生一行。
Pandas 中转换此数据集的最简单方法是什么
Class Students
0 1 A
1 1 B
2 1 C
3 1 D
4 1 E
5 2 F
6 2 G
7 2 H
喜欢这个新东西吗?
Class Students
0 1 A,B
1 1 A,C
2 1 A,D
3 1 A,E
4 1 B,C
5 1 B,D
6 1 B,E
7 1 C,D
6 1 B,E
8 1 C,D
9 1 C,E
10 1 D,E
11 2 F,G
12 2 F,H
12 2 G,H
试试这个:
import itertools
import pandas as pd
cla = [1, 1, 1, 1, 1, 2, 2, 2]
s = ["A", "B", "C", "D" , "E", "F", "G", "H"]
df = pd.DataFrame(cla, columns=["Class"])
df['Student'] = s
def create_combos(list_students):
combos = itertools.combinations(list_students, 2)
str_students = []
for i in combos:
str_students.append(str(i[0])+","+str(i[1]))
return str_students
def iterate_df(class_id):
df_temp = df.loc[df['Class'] == class_id]
list_student = list(df_temp['Student'])
list_combos = create_combos(list_student)
list_id = [class_id for i in list_combos]
return list_id, list_combos
list_classes = set(list(df['Class']))
new_id = []
new_combos = []
for idx in list_classes:
tmp_id, tmp_combo = iterate_df(idx)
new_id += tmp_id
new_combos += tmp_combo
new_df = pd.DataFrame(new_id, columns=["Class"])
new_df["Student"] = new_combos
print(new_df)