大 pandas 将某些列转换为行 [英] pandas convert some columns into rows

问题描述

因此，我的数据集包含一些有关n个日期的信息.问题在于每个日期实际上是一个不同的列标题.例如，CSV看起来像

So my dataset has some information by location for n dates. The problem is each date is actually a different column header. For example the CSV looks like

location    name    Jan-2010    Feb-2010    March-2010
A           "test"  12          20          30
B           "foo"   18          20          25

我想要的是它的外观

location    name    Date        Value
A           "test"  Jan-2010    12       
A           "test"  Feb-2010    20
A           "test"  March-2010  30
B           "foo"   Jan-2010    18       
B           "foo"   Feb-2010    20
B           "foo"   March-2010  25

问题是我不知道列中有多少个日期(尽管我知道它们总是以名字开头)

problem is I don't know how many dates are in the column (though I know they will always start after name)

推荐答案

更新
从v0.20开始，melt是一阶函数，您现在可以使用

UPDATE
From v0.20, melt is a first order function, you can now use

df.melt(id_vars=["location", "name"], 
        var_name="Date", 
        value_name="Value")

  location    name        Date  Value
0        A  "test"    Jan-2010     12
1        B   "foo"    Jan-2010     18
2        A  "test"    Feb-2010     20
3        B   "foo"    Feb-2010     20
4        A  "test"  March-2010     30
5        B   "foo"  March-2010     25

---

OLD(ER)VERSIONS:< 0.20

您可以使用 pd.melt 来获取大部分方式，然后排序:

You can use pd.melt to get most of the way there, and then sort:

>>> df
  location  name  Jan-2010  Feb-2010  March-2010
0        A  test        12        20          30
1        B   foo        18        20          25
>>> df2 = pd.melt(df, id_vars=["location", "name"], 
                  var_name="Date", value_name="Value")
>>> df2
  location  name        Date  Value
0        A  test    Jan-2010     12
1        B   foo    Jan-2010     18
2        A  test    Feb-2010     20
3        B   foo    Feb-2010     20
4        A  test  March-2010     30
5        B   foo  March-2010     25
>>> df2 = df2.sort(["location", "name"])
>>> df2
  location  name        Date  Value
0        A  test    Jan-2010     12
2        A  test    Feb-2010     20
4        A  test  March-2010     30
1        B   foo    Jan-2010     18
3        B   foo    Feb-2010     20
5        B   foo  March-2010     25

(可能想扔一个.reset_index(drop=True)，只是为了保持输出整洁.)

(Might want to throw in a .reset_index(drop=True), just to keep the output clean.)

注意:pd.DataFrame.sort 已弃用支持 pd.DataFrame.sort_values .

Note: pd.DataFrame.sort has been deprecated in favour of pd.DataFrame.sort_values.

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