CODEWITHSUNDEEP
pythonpandasdataframe
Mervyn Lee
Mervyn Lee

Reputation: 2187

Generate different random numbers to multiple rows in a column

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 )

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)

Example Data:

                                           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

EDIT

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

Upvotes: 3

Views: 1072

Answers (1)

WNG
WNG

Reputation: 3795

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]))

will give you what you want

Upvotes: 1

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