使用Pandas将数据框内的变量拆分为行 [英] Splitting variables within dataframe into rows using pandas

问题描述

我在这里看到过类似的问题，但似乎无法为我的数据获得正确的输出.我有一个看起来像这样的熊猫数据框:

I've seen similar questions asked here, but I can't seem to get the right output for my data. I have a pandas dataframe that looks like this:

   pm_code                   sec_pm                    site_no       state
0  010_628 010_228 015_634   2543677 2543677 2543677   010228955     me

我想将每个单元格分成多行(按空格分割)，并按state和site_no进行索引.

I'd like to break each cell into multiple rows (split by space) and indexed by state and site_no.

感谢您的帮助！

推荐答案

使用str.split拆分前两列并提取其值.

Split the first two columns using str.split and extract its values.

x = df.iloc[:, :2].applymap(str.split).values.tolist()[0]
x = list(zip(*x))

现在，获取最后两列并对其进行扩展以匹配拆分后前两列的值.

Now, take the last two columns and extend them to match the values of the first two columns post split.

y = np.repeat(df.iloc[:, -2:].values[:, ::-1], len(x), axis=0) 

现在，创建您的数据框.

Now, create your dataframe.

df2 = pd.DataFrame(x, index=y, columns=df.columns[:2])
df2    
                pm_code   sec_pm
(me, 10228955)  010_628  2543677
(me, 10228955)  010_228  2543677
(me, 10228955)  015_634  2543677

---

如果要使用MultiIndex，则需要致电pd.MultiIndex:

---

If you want a MultiIndex instead, you'd need to call pd.MultiIndex:

# https://stackoverflow.com/a/45946551/4909087
df2 = pd.DataFrame(x, index=pd.MultiIndex.from_arrays(y.T), columns=df.columns[:2])
df2
             pm_code   sec_pm
me 10228955  010_628  2543677
   10228955  010_228  2543677
   10228955  015_634  2543677

这篇关于使用Pandas将数据框内的变量拆分为行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！