使用适当的列值将pandas.core.series.Series转换为数据框python [英] Converting pandas.core.series.Series to dataframe with appropriate column values python

问题描述

我正在运行一个函数，其中的变量是pandas.core.series.Series类型.

i'm running a function in which a variable is of pandas.core.series.Series type.

type of the series shown below.

<class 'pandas.core.series.Series'>
product_id_y    1159730
count                 1
Name: 6159402, dtype: object

我想将其转换为数据框，这样我得到

i want to convert this into a dataframe,such that, i get

product_id_y    count
1159730           1

我尝试这样做:

series1 = series1.to_frame()

但得到错误的结果

转换为数据框后

              6159402
product_id_y  1159730
count               1

执行重置索引后，我为series1 = series1.reset_index()

after doing reset index i'e series1 = series1.reset_index()

           index  6159402
 0  product_id_y  1159730
 1         count        1

还有其他其他方法吗?

推荐答案

您非常亲密，首先

You was very close, first to_frame and then transpose by T:

s = pd.Series([1159730, 1], index=['product_id_y','count'], name=6159402)
print (s)
product_id_y    1159730
count                 1
Name: 6159402, dtype: int64

df = s.to_frame().T
print (df)
         product_id_y  count
6159402       1159730      1

---

df = s.rename(None).to_frame().T
print (df)
   product_id_y  count
0       1159730      1

使用DataFrame构造函数的另一种解决方案:

Another solution with DataFrame constructor:

df = pd.DataFrame([s])
print (df)
         product_id_y  count
6159402       1159730      1

---

df = pd.DataFrame([s.rename(None)])
print (df)
   product_id_y  count
0       1159730      1

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