假设
A='First'
B='Random'
C='Degree'
D='Largest'
A='Second'
B='Odd'
C='Inclined'
D='Maximum'
A='Third'
B='Even'
C='Steep'
D='Smallest'
A='Fourth'
B='Prime'
C='Gradient'
D='Minimum'
c = ['Group', 'Number', 'Angle', 'Max value']
df = pd.DataFrame([[A, B, C, D]], columns=c)
print (df)
#to csv
df.to_csv('Output.csv', encoding='utf-8', index=False)
实际输出:
它只显示最后一个输出,而不是每个值。像这样,如果有 N 个值,csv 必须存储所有 N 个值,一个在另一个值下
Group Number Angle Max Value
Fourth Prime Gradient Minimum
预期输出:
请您参考如下方法:
您应该遵循以下程序:
首先列出所有列,如下所示:
A = ['First', 'Random', 'Degree', 'Largest']
B = ['Second', 'Odd', 'Inclined', 'Maximum']
C = ['Third', 'Even', 'Steep', 'Smallest']
D = ['Fourth', 'Prime', 'Gradient', 'Minimum']
然后
c = ['Group', 'Number', 'Angle', 'Max value']
df = pd.DataFrame([A, B, C, D], columns=c)
print (df)
#to csv
df.to_csv('Output.csv', encoding='utf-8', index=False)
输出:
Group Number Angle Max value
0 First Random Degree Largest
1 Second Odd Inclined Maximum
2 Third Even Steep Smallest
3 Fourth Prime Gradient Minimum
