for i in range(df.shape[0]): df.iloc[i, 1] = timeChangeintoshixi(df.iloc[i, 1])对于以上代码,如何改造成一个多线程的代码,从而提高for循环速度
时间: 2024-01-22 22:17:16 浏览: 41
以下是将代码改造成多线程的示例:
```
import threading
def timeChangeintoshixi_thread(df, start, end):
for i in range(start, end):
df.iloc[i, 1] = timeChangeintoshix(df.iloc[i, 1])
def timeChangeintoshixi_multithread(df):
num_threads = 4 # 可以根据具体情况调整线程数
chunk_size = int(df.shape[0]/num_threads)
threads = []
for i in range(num_threads):
start = i * chunk_size
end = start + chunk_size
if i == num_threads - 1:
end = df.shape[0]
t = threading.Thread(target=timeChangeintoshixi_thread, args=(df, start, end))
t.start()
threads.append(t)
for t in threads:
t.join()
timeChangeintoshixi_multithread(df)
```
这里定义了一个 `timeChangeintoshixi_thread` 函数,它用于处理每个线程的数据。然后,定义了一个 `timeChangeintoshixi_multithread` 函数,它启动了多个线程并等待它们运行完毕。根据具体情况,可以调整线程数。