如何在Python中以正确的方式将一列分为2个？ [英] How can I split a column into 2 in the correct way in Python?

问题描述

我正在从网站上通过网络抓取表格，并将其放入Excel文件中。我的目标是以正确的方式将列分为2列。

I am web-scraping tables from a website, and I am putting it to the Excel file. My goal is to split a columns into 2 columns in the correct way.

我要拆分的列： STATUS

The columns what i want to split: "STATUS"

我想要这种形式：

第一个示例：估计下午3:17->估计下午3:17

First example: Estimated 3:17 PM --> Estimated and 3:17 PM

第二个示例：延迟3:00 PM->延迟和3:00 PM

Second example: Delayed 3:00 PM --> Delayed and 3:00 PM

第三个示例：取消->取消和（空单元格）

Third example: Canceled --> Canceled and (empty cell)

因此，我需要分隔第一个单词（在第一列中），然后分隔下一个字符。

So, I need to separete the FIRST word (in the first column), and after that the next characters.

我该怎么做？

这里是我的相关代码，该代码已经包含格式化代码。

Here my relevant code, which is already contains a formatting code.

df2 = pd.DataFrame(datatable,columns = cols)
df2['a'] = df2['FLIGHT'].str[:2]
df2['b'] = df2['FLIGHT'].str[2:].str.zfill(4)
df2["UPLOAD_TIME"] = datetime.now()
mask = np.column_stack([df2[col].astype(str).str.contains(r"Scheduled", na=True) for col in df2])
df3 = df2.loc[~mask.any(axis=1)] 

if os.path.isfile("output.csv"):
    df1 = pd.read_csv("output.csv", sep=";")
    df4 = pd.concat([df1,df3])
    df4.to_csv("output.csv", index=False, sep=";")

else:
    df3.to_csv
    df3.to_csv("output.csv", index=False, sep=";")

这是我表中的excel prt sc：

Here the excel prt sc from my table:

推荐答案

您可以使用 str。拆分 - n = 1 用于按第一个空格和 expand = True 返回 DataFrame ，可以将其分配给新列：

You can use str.split - n=1 for split by first whitespace and expand=True for return DataFrame, which can be assign to new columns:

df2[['c','d']] = df2['STATUS'].str.split(n=1, expand=True)

示例：

df2 = pd.DataFrame({'STATUS':['Estimated 3:17 PM','Delayed 3:00 PM']})


df2[['c','d']] = df2['STATUS'].str.split(n=1, expand=True)
print (df2)
              STATUS          c        d
0  Estimated 3:17 PM  Estimated  3:17 PM
1    Delayed 3:00 PM    Delayed  3:00 PM

---

如果输入中没有空格，则输出中没有 ：

df2 = pd.DataFrame({'STATUS':['Estimated 3:17 PM','Delayed 3:00 PM', 'Canceled']})


df2[['c','d']] = df2['STATUS'].str.split(n=1, expand=True)
print (df2)
              STATUS          c        d
0  Estimated 3:17 PM  Estimated  3:17 PM
1    Delayed 3:00 PM    Delayed  3:00 PM
2           Canceled   Canceled     None

，如果需要替换无来清空字符串，请使用 fillna ：

and if need replace None to empty string use fillna:

df2[['c','d']] = df2['STATUS'].str.split(n=1, expand=True)
df2['d'] = df2['d'].fillna('')
print (df2)
              STATUS          c        d
0  Estimated 3:17 PM  Estimated  3:17 PM
1    Delayed 3:00 PM    Delayed  3:00 PM
2           Canceled   Canceled         

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