使用if语句重建pandas Dataframe [英] Rebuild pandas Dataframe with if Statements

问题描述

正如在另一个问题中已经问到的那样，标题为"Rebuild pandas Dataframe".我还有关于继续使用更多列的一些问题.

As allready asked in another Question with the Title "Rebuild pandas Dataframe" i still have some Questions about going on with even more columns.

情况: 我有一个带有4列的数据框，这些列中的值是相当随机的.如以下示例:

Situation: I have a Dataframe with 4 Columns, the Values inside the Columns are pretty Random. Such as this example:

df = pd.DataFrame({'col1': ['id 1', 'id 2', 'test 3', 'test 4'],
           'col2': ['test 1', 'test 2',
                    'ne 5261', 'id 4'],
           'col3': ['Number 12344', 'Number 21612','id 3','Number 1131'],
           'col4':['ne 315','Number 1264777','ne 1415','ne 52']})

我的目标是拥有一个数据框，其中每个Col仅具有以Same子字符串开头的值，例如以下示例:

My Goal is to have a Dataframe in which each Col has only the Values beginning with the Same substring like this example:

下面的代码(已从最后一个问题"致谢:@AndrejKesely)变为了以下三列的有用代码:

What already worked for 3 columns is the following code (from The last Question credits to: @AndrejKesely):

def key_fn(x):
if 'id' in x:
    return 0
if 'test' in x:
    return 1
if 'Number' in x:
    return 2
return 3
df = pd.DataFrame([sorted(l, key=key_fn) for l in df.values], columns=df.columns)

print(df)

由于我现在有4个列，因此我向函数添加了另一个if语句，如下所示:

Since i now have 4 cols i added another if Statement to the Function, looking as follows:

def key_fn(x):
if 'id' in x:
    return 0
if 'test' in x:
    return 1
if 'Number' in x:
    return 2
if 'ne' in x:
    return 3
return 4
df = pd.DataFrame([sorted(l, key=key_fn) for l in df.values], columns=df.columns)

这给了我以下输出:

这是一个小例子，当我了解它是如何工作的时，我需要将其应用于总共17列. 预先感谢您的帮助！

This is a small example, when i understand how it works i need to apply it to a Total of 17 Columns. Thank you in advance for your Help!

推荐答案

df = pd.DataFrame({'col1': ['id 1', 'id 2', 'test 3', 'test 4'],
           'col2': ['test 1', 'test 2',
                    'ne 5261', 'id 4'],
           'col3': ['Number 12344', 'Number 21612','id 3','Number 1131'],
           'col4':['ne 315','Number 1264777','ne 1415','ne 52']})

def key_fn(x):
    if 'id' in x:
        return 0
    if 'test' in x:
        return 1
    if 'Number' in x:
        return 2
    if 'ne' in x:
        return 3
    return 4

out_df = pd.DataFrame(np.array(sorted(np.ravel(df.values), key=key_fn)).reshape(df.shape), columns=df.columns).T
print(out_df)

打印:

   col1    col2            col3     col4
0  id 1  test 1    Number 12344   ne 315
1  id 2  test 2    Number 21612  ne 5261
2  id 3  test 3  Number 1264777  ne 1415
3  id 4  test 4     Number 1131    ne 52

这篇关于使用if语句重建pandas Dataframe的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！