Reputation: 19375
I have a dataframe that is indexed according to the following variables: NAME - date. Name is some sort of bizarre ID, and date is.. a date.
The data is very large and I would like to inspect the data I have for several random choices of NAME.
That is,
I dont know how to do that. I see that we can use get_level_values
, but I dont have a specific NAME in mind, I just want to call random samples many times.
Any help appreciated! Thanks!
Upvotes: 3
Views: 1505
Reputation: 36545
You could forget your multi-index, and just use isin
with sample
:
import random
df = df.reset_index()
df[df['NAME'].isin(random.sample(list(df['NAME'].unique()),5))]
Upvotes: 1
Reputation: 18913
import pandas as pd
import numpy as np
import random
import string
df = pd.DataFrame(data={'NAME': [''.join(random.choice(string.ascii_uppercase + string.ascii_lowercase + string.digits) for _ in range(17)) for _ in range(10)],
'Date': pd.date_range('1/01/2016', periods=10),
'Whatever': np.random.randint(20, 50, 10)},
columns=['NAME', 'Date', 'Whatever']).set_index(['NAME', 'Date'])
random_df = df[df.index.get_loc(np.random.choice(df.index.levels[0])) == True].sort_index(level=1)
print(random_df)
Returns a df
that looks like this:
Whatever
NAME Date
xg71zOEQVOEfCZ2ne 2016-01-01 35
qLCXuEerCXi6gmF1Y 2016-01-02 26
0vDe7x8TIb5FRv7hV 2016-01-03 40
Ddc6FGKBdtcLqT53O 2016-01-04 31
IYcrKG9pjt7mHH3qn 2016-01-05 44
lAWObNTC8yXPMY3v5 2016-01-06 49
k90QWdPc5qFSCFi1c 2016-01-07 22
BWQoHo8lUyEwK9Nuf 2016-01-08 42
Xt0bxUerTan0i1eGw 2016-01-09 22
tc7PYCzpyGmYLbnxu 2016-01-10 46
A random_df
that looks like this:
Whatever
NAME Date
IYcrKG9pjt7mHH3qn 2016-01-05 44
Upvotes: 2