带for循环的数据帧索引

Question

这是昨天那个问题的后续问题。我有一个由csv文件创建的数据帧，我正在尝试比较当前值和下一个值。如果他们是一样的，我做一件事，否则，我做另一件事。我遇到了一个超出范围的问题，希望能找到一个解决办法。在

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）：

^{pr2}$

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

不是一条线，而是更好的

^{pr2}$

相同的答案，但正在更新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找到了看到错误的原因。在

不过，我猜你想做什么。
我把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

我想你的for循环只需要一个索引

尝试：

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

取而代之的是

编辑： 有道理的是：

new_fruit = old_fruit[x+1]

并没有给出预期的结果，老嫒果不是一个列表而是一个字符串。我想你想要的是：

new_fruit = df.fruit[x+1]

编辑（2）：

您应该添加： 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)