Python 依次将 2 个列表和 Pandas 个数据帧写入 csv/excel
Python write 2 lists and Pandas DataFrames to csv/excel sequentially
我有这些 Python 列表和 Pandas 数据框:
list_1 = ['Intro line here - record of method function:']
list_2 = ['Record of local minimum follows:']
print df_1
Col_A Col_B
3.4443 1.443
10.8876 11.99
print df2
Trial_1 Trial_2 Trial_3
1.1 1.49 775.9
11.5 9.57 87.3
384.61 77.964 63.7
12.49 0.156 1.9
112.11 11.847 178.3
这是我想要的输出 csv 或 excel 文件 - csv 或 excel 都适合我:
Intro line here - record of method function:
Col_A Col_B
3.4443 1.443
10.8876 11.99
Record of local minimum follows:
Trial_1 Trial_2 Trial_3
1.1 1.49 775.9
11.5 9.57 87.3
384.61 77.964 63.7
12.49 0.156 1.9
112.11 11.847 178.3
有没有办法把list,Pandas,list,Pandas按这个顺序写入csv或者excel文件?
csv module 提供您想要的功能:
import csv
with open('SO Example.csv', 'w') as f:
writer = csv.writer(f, lineterminator='\n')
writer.writerow(list_1)
writer.writerow(df1.columns)
writer.writerows(df1.values)
writer.writerow(list_2)
writer.writerow(df2.columns)
writer.writerows(df2.values)
pd.to_csv()
接受文件句柄作为输入,而不仅仅是文件名。所以你可以打开一个文件句柄并将多个文件写入其中。这是一个例子:
from __future__ import print_function
with open('output.csv', 'w') as handle:
for line in list_1:
print(line, handle)
df1.to_csv(handle, index=False)
for line in list_2:
print(line, handle)
df2.to_csv(handle, index=False)
我有这些 Python 列表和 Pandas 数据框:
list_1 = ['Intro line here - record of method function:']
list_2 = ['Record of local minimum follows:']
print df_1
Col_A Col_B
3.4443 1.443
10.8876 11.99
print df2
Trial_1 Trial_2 Trial_3
1.1 1.49 775.9
11.5 9.57 87.3
384.61 77.964 63.7
12.49 0.156 1.9
112.11 11.847 178.3
这是我想要的输出 csv 或 excel 文件 - csv 或 excel 都适合我:
Intro line here - record of method function:
Col_A Col_B
3.4443 1.443
10.8876 11.99
Record of local minimum follows:
Trial_1 Trial_2 Trial_3
1.1 1.49 775.9
11.5 9.57 87.3
384.61 77.964 63.7
12.49 0.156 1.9
112.11 11.847 178.3
有没有办法把list,Pandas,list,Pandas按这个顺序写入csv或者excel文件?
csv module 提供您想要的功能:
import csv
with open('SO Example.csv', 'w') as f:
writer = csv.writer(f, lineterminator='\n')
writer.writerow(list_1)
writer.writerow(df1.columns)
writer.writerows(df1.values)
writer.writerow(list_2)
writer.writerow(df2.columns)
writer.writerows(df2.values)
pd.to_csv()
接受文件句柄作为输入,而不仅仅是文件名。所以你可以打开一个文件句柄并将多个文件写入其中。这是一个例子:
from __future__ import print_function
with open('output.csv', 'w') as handle:
for line in list_1:
print(line, handle)
df1.to_csv(handle, index=False)
for line in list_2:
print(line, handle)
df2.to_csv(handle, index=False)