使用 DataFrame 我想添加一个将写入 Field1、Field2 的列...(包含与索引 1 一样多的行)
Using DataFrame I want to add a column that will write Field1, Field2...(containing as many rows as the index-1)
我想使用 DataFrame 添加一个列来写入 Field1、Field2...(包含与索引 1 一样多的行)。
import numpy as np
df = pd.DataFrame(list(zip(total_points, passing_percentage)),
columns =['Pts_Measured', '%_pass'])
df = df.rename_axis('Field').reset_index()
df["Comments"] = ""
df["Field"] = np.arange(1, len(df) + 1)
df
输出:
Field Pts_Measured %_pass Comments
0 1 92909 90.66
1 2 92830 91.85
2 3 130714 99.99
这就是我想要的:
Field Field_num Pts_Measured %_pass Comments
0 1 Field1 92909 90.66
1 2 Field2 92830 91.85
2 3 FIeld3 130714 99.99
.. .... ............ .......... .......
希望我已经正确理解您的问题。如果你有这个数据框:
Pts_Measured %_pass Comments
0 1 92909 90.66
1 2 92830 91.85
2 3 130714 99.99
那么你可以这样做:
df["Field"] = np.arange(len(df)) + 1
df["Field_num"] = "Field" + df["Field"].astype(str)
print(df)
打印:
Pts_Measured %_pass Comments Field Field_num
0 1 92909 90.66 1 Field1
1 2 92830 91.85 2 Field2
2 3 130714 99.99 3 Field3
我想使用 DataFrame 添加一个列来写入 Field1、Field2...(包含与索引 1 一样多的行)。
import numpy as np
df = pd.DataFrame(list(zip(total_points, passing_percentage)),
columns =['Pts_Measured', '%_pass'])
df = df.rename_axis('Field').reset_index()
df["Comments"] = ""
df["Field"] = np.arange(1, len(df) + 1)
df
输出:
Field Pts_Measured %_pass Comments
0 1 92909 90.66
1 2 92830 91.85
2 3 130714 99.99
这就是我想要的:
Field Field_num Pts_Measured %_pass Comments
0 1 Field1 92909 90.66
1 2 Field2 92830 91.85
2 3 FIeld3 130714 99.99
.. .... ............ .......... .......
希望我已经正确理解您的问题。如果你有这个数据框:
Pts_Measured %_pass Comments
0 1 92909 90.66
1 2 92830 91.85
2 3 130714 99.99
那么你可以这样做:
df["Field"] = np.arange(len(df)) + 1
df["Field_num"] = "Field" + df["Field"].astype(str)
print(df)
打印:
Pts_Measured %_pass Comments Field Field_num
0 1 92909 90.66 1 Field1
1 2 92830 91.85 2 Field2
2 3 130714 99.99 3 Field3