Question

这是昨天的一个跟进问题。我有一个由csv文件创建的数据框，我试图比较当前和下一个值。如果他们是相同的，我做一件事，否则，我做另一件事。我正在达到一个超出范围的问题，并希望我能找到一个解决方法。

CSV：

date    fruit   quantity
4/5/2014 13:34  Apples  73
4/5/2014 3:41   Cherries    85
4/6/2014 12:46  Pears   14
4/8/2014 8:59   Oranges 52
4/10/2014 2:07  Apples  152
4/10/2014 18:10 Bananas 23
4/10/2014 2:40  Strawberries    98

预期输出CSV（备份CSV）：

date    fruit   quantity fruitid 
4/5/2014 13:34  Apples  73 fruit0
4/5/2014 3:41   Cherries    85 fruit1
4/6/2014 12:46  Pears   14 fruit2
4/8/2014 8:59   Oranges 52 fruit3
4/10/2014 2:07  Apples  152 fruit0
4/10/2014 18:10 Bananas 23 fruit4
4/10/2014 2:40  Strawberries    98 fruit5

最终CSV：

date    fruitid quantity  
    4/5/2014 13:34  fruit0  73 
    4/5/2014 3:41   fruit1  85 
    4/6/2014 12:46  fruit2  14 
    4/8/2014 8:59   fruit3  52 
    4/10/2014 2:07  fruit0  152 
    4/10/2014 18:10 fruit4  23 
    4/10/2014 2:40  fruit5  98

代码：

import pandas as pd
import numpy
df = pd.read_csv('example2.csv', header=0, dtype='unicode')
df_count = df['fruit'].value_counts()
df.sort_values(['fruit'], ascending=True, inplace=True) #sorting the column 
#fruit
df.reset_index(drop=True, inplace=True)
#print(df)
x = 0 #starting my counter values or position in the column
#old_fruit = df.fruit[x]
#new_fruit = df.fruit[x+1]
df.loc[:,'NewCol'] = 0 # to create the new column
print(df)
for x in range(0, len(df)):
        old_fruit = df.fruit[x] #Starting fruit
        new_fruit = old_fruit[x+1] #next fruit to compare with
        if old_fruit == new_fruit:
                #print(x)
                #print(old_fruit, new_fruit)
                df.NewCol[x] = 'fruit' + str(x) #if they are the same, put 
                #fruit[x] or fruit0 in the current row

        else:
                print("Not the Same")
                #print(x)
                #print(old_fruit, new_fruit)
                df.NewCol[x+1] = 'fruit' +str(x+1) #if they are the same, 
                #put fruit[x+1] or fruit1 in the current row
print(df)

Answer 1

新答案

使用factorize

df.assign(
    NewCol=np.core.defchararray.add('Fruit', df.fruit.factorize()[0].astype(str))
)

              date         fruit  quantity  NewCol
0   4/5/2014 13:34        Apples        73  Fruit0
1    4/5/2014 3:41      Cherries        85  Fruit1
2   4/6/2014 12:46         Pears        14  Fruit2
3    4/8/2014 8:59       Oranges        52  Fruit3
4   4/10/2014 2:07        Apples       152  Fruit0
5  4/10/2014 18:10       Bananas        23  Fruit4
6   4/10/2014 2:40  Strawberries        98  Fruit5

不是一行，而是更好

f, u = pd.factorize(df.fruit.values)
n = np.core.defchararray.add('Fruit', f.astype(str))
df.assign(NewCol=n)

              date         fruit  quantity  NewCol
0   4/5/2014 13:34        Apples        73  Fruit0
1    4/5/2014 3:41      Cherries        85  Fruit1
2   4/6/2014 12:46         Pears        14  Fruit2
3    4/8/2014 8:59       Oranges        52  Fruit3
4   4/10/2014 2:07        Apples       152  Fruit0
5  4/10/2014 18:10       Bananas        23  Fruit4
6   4/10/2014 2:40  Strawberries        98  Fruit5

相同的答案，但更新df

f, u = pd.factorize(df.fruit.values)
n = np.core.defchararray.add('Fruit', f.astype(str))
df = df.assign(NewCol=n)
# Equivalent to
# df['NewCol'] = n
df

              date         fruit  quantity  NewCol
0   4/5/2014 13:34        Apples        73  Fruit0
1    4/5/2014 3:41      Cherries        85  Fruit1
2   4/6/2014 12:46         Pears        14  Fruit2
3    4/8/2014 8:59       Oranges        52  Fruit3
4   4/10/2014 2:07        Apples       152  Fruit0
5  4/10/2014 18:10       Bananas        23  Fruit4
6   4/10/2014 2:40  Strawberries        98  Fruit5

旧答案

@SeaMonkey指出了看到错误的原因。

然而，我猜你在做什么我将cumcount添加到fruit

df.assign(NewCol=df.fruit + df.groupby('fruit').cumcount().astype(str))

              date         fruit  quantity         NewCol
0   4/5/2014 13:34        Apples        73        Apples0
1    4/5/2014 3:41      Cherries        85      Cherries0
2   4/6/2014 12:46         Pears        14         Pears0
3    4/8/2014 8:59       Oranges        52       Oranges0
4   4/10/2014 2:07        Apples       152        Apples1
5  4/10/2014 18:10       Bananas        23       Bananas0
6   4/10/2014 2:40  Strawberries        98  Strawberries0

Answer 2

我认为你的for循环是一个索引到远，

尝试：

for x in range(0, len(df)-1):

代替

修改这是有意义的：

new_fruit = old_fruit[x+1]

没有给出预期的结果，old_fruit不是列表而是字符串。我想你想要的是：

new_fruit = df.fruit[x+1]

修改（2）：

你应该补充： df.NewCol[x+1] = 'fruit' + str(x)

我的工作脚本是：

import pandas as pd import numpy df = pd.read_csv('data.csv', header=0, dtype='unicode') df_count = df['fruit'].value_counts() df.sort_values(['fruit'], ascending=True, inplace=True) #sorting the column #fruit df.reset_index(drop=True, inplace=True) #print(df) x = 0 #starting my counter values or position in the column #old_fruit = df.fruit[x] #new_fruit = df.fruit[x+1] df.loc[:,'NewCol'] = 0 # to create the new column print(df) for x in range(0, len(df)-1): old_fruit = df.fruit[x] #Starting fruit new_fruit = df.fruit[x+1] #next fruit to compare with if old_fruit == new_fruit: #print(x) #print(old_fruit, new_fruit) df.NewCol[x] = 'fruit' + str(x) df.NewCol[x+1] = 'fruit' + str(x)#if they are the same, put #fruit[x] or fruit0 in the current row else: print("Not the Same") #print(x) #print(old_fruit, new_fruit) df.NewCol[x+1] = 'fruit' +str(x+1) #if they are the same, #put fruit[x+1] or fruit1 in the current row print(df)

使用for循环进行数据帧索引

2 个答案: