我在写入文本文件时遇到问题。这是我的代码段。
ram_array= map(str, ram_value)
cpu_array= map(str, cpu_value)
iperf_ba_array= map(str, iperf_ba)
iperf_tr_array= map(str, iperf_tr)
#with open(ram, 'w') as f:
#for s in ram_array:
#f.write(s + '\n')
#with open(cpu,'w') as f:
#for s in cpu_array:
#f.write(s + '\n')
with open(iperf_b,'w') as f:
for s in iperf_ba_array:
f.write(s+'\n')
f.close()
with open(iperf_t,'w') as f:
for s in iperf_tr_array:
f.write(s+'\n')
f.close()
ram和cpu都可以完美地工作,但是当写入iperf_ba和iperf_tr的文件时,它们总是出现如下:
[45947383.0, 47097609.0, 46576113.0, 47041787.0, 47297394.0]
而不是
1
2
3
他们都是从全球名单中读取的。 cpu和ram具有逐个附加的值,但是否则它们看起来完全相同的预处理。
以下是他们的制作方式
filename= "iperfLog_2015_03_12_20:45:18_123_____tag_33120L06.csv"
write_location= self.tempLocation()
location=(str(write_location) + str(filename));
df = pd.read_csv(location, names=list('abcdefghi'))
transfer = df.h
transfer=transfer[~transfer.isnull()]#uses pandas to remove nan
transfer=transfer.tolist()
length= int(len(transfer))
extra= length-1
del transfer[extra]
bandwidth= df.i
bandwidth=bandwidth[~bandwidth.isnull()]
bandwidth=bandwidth.tolist()
del bandwidth[extra]
iperf_tran.append(transfer)
iperf_band.append(bandwidth)
答案 0 :(得分:1)
[来自评论]
如果你想在列表中添加一个列表,你需要使用.extend(list) - 并且不用担心:我们有时会花费数小时调试/追逐优雅 - 愚蠢的错误; )