我想知道在尝试将加载数据创建到变量Fluence_rates
时是否还有其他Python方式或我没有使用的工具。
我正在尝试:
openfiles1 = eg.fileopenbox("Select the files for analysis", filetypes= "*.txt", multiple=True)
Fluence_rates = np.array([])
Fluence_rates = np.split(Fluence_rates,len(openfiles1))
count = -1
for item in reversed(openfiles1):
count+=1
f1 = pd.read_csv(item, sep='delimiter')
f_trim_1 = f1[17:]
f_trim_1 = f_trim_1.replace({'\t':' '},regex=True)
f_trim_1.columns = ['all_cols']
new_df_1 = pd.DataFrame(list(f_trim_1.all_cols.apply(str.split)), columns=['time','Total JPercm^2','mwPercmSq','JPercm2','IP Index','detectorDASHsource','Source CH','Raw Counts'])
Flues= new_df_1.mwPercmSq.values
Fluence_rates[count] = Flues
可以正确填充Fluence_rates,但是想知道是否还有更Python化的方法来实现此目的?