为一列中的多行生成不同的随机数 [英] Generate different random numbers to multiple rows in a column

问题描述

我有一列具有整数值(n行).我想生成一个随机数，其范围从满足某些条件的值的正态分布开始.我尝试使用下面的代码，但是它们太慢了.

I got a columns with integer values(n rows). I want to generate random numbers that range from a normal distribution on values that meet certain condition. I tried with code below but they are too slow.

df_members['bd'] = df_members.bd.apply(lambda x: np.random.normal(bd_mean, bd_sd) if float(x)==-99999 else x )

我尝试使用下面的代码，但它只会为所有行分配一个随机值.

I tried with code below but it will only assign one random value to all the rows.

bd_mean = 29.2223808862
bd_std = 10.4168850957
df_members[df_members['bd'] == -99999] = np.random.normal(bd_mean, bd_sd)

示例数据:

                                           msno  city     bd  gender  registered_via
0  URiXrfYPzHAlk+7+n7BOMl9G+T7g8JmrSnT/BU8GmEo=     1 -99999     NaN               9
1  U1q0qCqK/lDMTD2kN8G9OXMtfuvLCey20OAIPOvXXGQ=     1     26     NaN               4
2  W6M2H2kAoN9ahfDYKo3J6tmsJRAeuFc9wl1cau5VL1Q=     1 -99999     NaN               4
3  1qE5+cN7CUyC+KFH6gBZzMWmM1QpIVW6A43BEm98I/w=     5     17  female               4
4  SeAnaZPI+tFdAt+r3lZt/B8PgTp7bcG/1os39u4pLxs=     1 -99999     NaN               4

编辑

我猜想生成3425689(行)个随机数会花费很长时间.此刻我将坚持第一种方式.

I guess that generating 3425689(rows) random numbers will take a long time. I will stick to the first way at this moment.

推荐答案

您丢失了，它将给出要生成的随机值的形状.

You're missing the "size" argument that will give the shape of the random values to be generated.

df_members[df_members['bd'] == -99999] = np.random.normal(bd_mean, bd_sd,len(df_members[df_members['bd'] == -99999])) 

会给您您想要的东西

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