使用numpy库的isnan()函数 numpy.isnan(x)函数可以判断给定的数据x是否为NaN。如果x是NaN,则返回True;否则返回False。 importnumpyasnp x=np.nanifnp.isnan(x):print("x is NaN")else:print("x is not NaN") 1. 2. 3. 4. 5. 6. 7. 运行以上代码,输出结果为x is NaN。 示例 假设我们有一组...
import math def quadratic(a, b, c): if a == 0: return "a不能等于0" d = b*b - 4*a*c if d < 0: return "此方程无解" result1 = (-b + math.sqrt(d))/(2*a) result2 = (-b - math.sqrt(d))/(2*a) return result1, result 1. 2. 3. 4. 5. 6. 7. 8. 9. 10...
importpandas as pdimportnumpy as npfrommathimportisnan data= [[1, 2, 3], ["a", None,"c"]] columns= ["A1","B1","C1"] df= pd.DataFrame(data=data, columns=columns)#使用python内置方法foriindf['B1'].values:ifisnan(i):print(True)#使用numpy的方法foriindf['B1'].values:ifnp.is...
values :column to aggregate, optional index :column, Grouper, array, or list of the previous . If an array is passed, it must be the same length as the data. The list can contain any of the other types (except list). Keys to group by on the pivot table index. If an array is pa...
defgreeting(name):iflen(name)>3:return_private_1(name)else:return_private_2(name) 我们在模块里公开greeting()函数,而把内部逻辑用private函数隐藏起来了,这样,调用greeting()函数不用关心内部的private函数细节,这也是一种非常有用的代码封装和抽象的方法,即: ...
(A),1): print(f'{f:18}',end='' if i%5 else '\n') factorize nbytes between to_list str argsort rdivmod argmax tolist item is_monotonic_increasingdt autocorr is_monotonic_decreasingview repeat name array map dtype divmod to_frame unique ravel searchsorted hasnans is_unique is_...
defas_complex(dct):if'__complex__'indct:returncomplex(dct['real'],dct['imag'])returndct # 使用自定义的恢复函数 # 自定义的恢复函数将real数据转换成复数的实部,将imag转换成复数的虚部 result3=json.loads('{"__complex__": true, "real": 1, "imag": 2}',\ ...
output_df = pd.DataFrame({'Values':[adft[0], adft[1], adft[4]['1%']],'Metric':['Test Statistics','p-value','critical value (1%)']})print('Statistics of {} sensor:\n'.format(sensor), output_df)print()if(adft[1] < 0.05) & (adft[0] < adft[4]['1%']):print('The...
处理订阅结果:t1=ticker1.time.timestamp()importnumpyasnpbidPrice=np.nan_to_num(ticker1.bid)# 买一价askPrice=np.nan_to_num(ticker1.ask)# 卖一价lastPrice=np.nan_to_num(ticker1.last)highPrice=np.nan_to_num(ticker1.high)whilehighPrice<=0:Log('行情异常:highPrice=',highPrice,'!')if...
18 章～第 20 章使用新版的 Django 创建“学习笔记”项目，并使用新版Bootstrap 设置样式；附录 A 做...