pytao
发表于 2022-4-4 14:35:51
{:9_241:}
andy大宝
发表于 2022-4-4 18:37:29
file是什么啊
andy大宝
发表于 2022-4-4 18:38:00
{:10_245:}
qq1151985918
发表于 2022-4-4 21:32:34
{:9_227:}
elven08
发表于 2022-4-5 09:26:00
我也处理过类似的,有点经验仅供参考,其实读取不慢,慢的是append和concat。
我采取的是循环读取,然后再concat。
隔壁老程呀
发表于 2022-4-5 09:42:31
加油
tiangtian
发表于 2022-4-5 18:15:59
怎么解决的?
1050293757
发表于 2022-4-10 20:40:17
{:5_109:}
AFAEGA
发表于 2022-4-11 10:15:53
{:7_146:}
a1372245671
发表于 2022-4-11 10:18:22
{:5_109:}
东方天晨
发表于 2022-4-11 19:38:25
???
我叫武炜昊
发表于 2022-4-11 19:38:57
???
QQ小鱼
发表于 2022-4-11 19:59:29
有钱人,加油
okamn
发表于 2022-4-11 20:14:04
不知道啊{:10_266:}
AFAEGA
发表于 2022-4-12 11:27:09
{:7_146:}
一身腱子肉
发表于 2022-4-12 17:21:51
路过进来学习,pandas优势在于数据处理(类似统计等),针对excel处理还是推荐openpyxl和xlwings
DetConan
发表于 2022-4-13 13:19:28
可以看看具体慢的是read还是concat
rsj0315
发表于 2022-4-14 08:17:59
10个文件,能不能试试多线程去读呢,def concat_file():
with concurrent.futures.ThreadPoolExecutor() as executor:
# with concurrent.futures.ProcessPoolExecutor() as executor:
f_451 = executor.submit(read_txt,path_45_1,'45-1')
f_452 = executor.submit(read_txt,path_45_2, '45-2')
f_651 = executor.submit(read_txt,path_65_1, '65-1')
f_120 = executor.submit(read_txt,path_120, '120')
f_ws = executor.submit(read_txt,path_wenshui, '温水')
f_1501 = executor.submit(read_txt,path_150_1, '150-1')
f_1502 = executor.submit(read_txt,path_150_2, '150-2')
df_451 = f_451.result()
df_452 = f_452.result()
df_651 = f_651.result()
df_120 = f_120.result()
df_ws = f_ws.result()
df_1501 = f_1501.result()
df_1502 = f_1502.result()
df = pd.concat()
songwentao
发表于 2022-4-14 08:54:50
加油
阿萨德按时
发表于 2022-4-14 10:17:49
{:10_254:}