pandas series sample - Brave Search

return the index using pandas series.sample()?

stackoverflow.com › questions › 45968529 › return-the-index-using-pandas-series-sample

As @user48956 commented on accepted answer, is much faster to sample over the index using numpy.random.choice

np.random.seed(42)
df = pd.DataFrame(np.random.randint(0,100,size=(10000000, 4)), columns=list('ABCD'))
%time df.sample(100000).index
print(_)
%time pd.Index(np.random.choice(df.index, 100000))

Wall time: 710 ms
Int64Index([7141956, 9256789, 1919656, 2407372, 9181191, 2474961, 2345700,
            4394530, 8864037, 6096638,
            ...
             471501, 3616956, 9397742, 6896140,  670892, 9546169, 4146996,
            3465455, 7748682, 5271367],
           dtype='int64', length=100000)
Wall time: 6.05 ms

Int64Index([7141956, 9256789, 1919656, 2407372, 9181191, 2474961, 2345700,
            4394530, 8864037, 6096638,
            ...
             471501, 3616956, 9397742, 6896140,  670892, 9546169, 4146996,
            3465455, 7748682, 5271367],
           dtype='int64', length=100000)

Answer from Ameb on Stack Overflow

pandas.pydata.org › docs › reference › api › pandas.Series.sample.html

pandas.Series.sample — pandas 3.0.5 documentation

Extract 3 random elements from the Series df['num_legs']: Note that we use random_state to ensure the reproducibility of the examples. >>> df["num_legs"].sample(n=3, random_state=1) fish 0 spider 8 falcon 2 Name: num_legs, dtype: int64

w3resource.com › pandas › series › series-sample.php

Pandas Series: sample() function - w3resource

May 13, 2026 - Example - Extract 3 random elements from the Series df['num_legs']: Note that we use random_state to ensure the reproducibility of the examples: ... import numpy as np import pandas as pd df = pd.DataFrame({'num_legs': [2, 4, 8, 0], 'num_wings': [2, 0, 0, 0], 'num_specimen_seen': [8, 2, 1, 6]}, index=['sparrow', 'cat', 'spider', 'snake']) df['num_legs'].sample(n=3, random_state=1)

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February 27, 2022

pandas.pydata.org › pandas-docs › stable › reference › api › pandas.Series.sample.html

pandas.Series.sample — pandas 2.3.3 documentation

Generates random samples from each group of a Series object.

geeksforgeeks.org › pandas › python-pandas-series-sample

Python | Pandas Series.sample() - GeeksforGeeks

February 7, 2019 - Example #2: Use Series.sample() function to draw random sample of the values from the given Series object. ... # importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([100, 25, 32, 118, 24, 65]) # Create the Index index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp'] # set the index sr.index = index_ # Print the series print(sr) Output : Now we will use Series.sample() function to select a random sample of size equivalent to 25% of the size of the given Series object...

pandas.pydata.org › pandas-docs › version › 0.23.4 › generated › pandas.Series.sample.html

pandas.Series.sample — pandas 0.23.4 documentation

Return a random sample of items from an axis of object. You can use random_state for reproducibility. ... >>> s = pd.Series(np.random.randn(50)) >>> s.head() 0 -0.038497 1 1.820773 2 -0.972766 3 -1.598270 4 -1.095526 dtype: float64 >>> df = pd.DataFrame(np.random.randn(50, 4), columns=list('ABCD')) ...

w3schools.com › python › pandas › pandas_series.asp

Data sets in Pandas are usually multi-dimensional tables, called DataFrames. Series is like a column, a DataFrame is the whole table.

pandas.pydata.org › pandas-docs › dev › reference › api › pandas.Series.sample.html

pandas.Series.sample — pandas 3.0.0.dev0+2650.g607e489bd1 documentation

Extract 3 random elements from the Series df['num_legs']: Note that we use random_state to ensure the reproducibility of the examples. >>> df["num_legs"].sample(n=3, random_state=1) fish 0 spider 8 falcon 2 Name: num_legs, dtype: int64

stackoverflow.com › questions › 45968529 › return-the-index-using-pandas-series-sample

python - return the index using pandas series.sample()? - Stack Overflow

As @user48956 commented on accepted answer, is much faster to sample over the index using numpy.random.choice

np.random.seed(42)
df = pd.DataFrame(np.random.randint(0,100,size=(10000000, 4)), columns=list('ABCD'))
%time df.sample(100000).index
print(_)
%time pd.Index(np.random.choice(df.index, 100000))

Wall time: 710 ms
Int64Index([7141956, 9256789, 1919656, 2407372, 9181191, 2474961, 2345700,
            4394530, 8864037, 6096638,
            ...
             471501, 3616956, 9397742, 6896140,  670892, 9546169, 4146996,
            3465455, 7748682, 5271367],
           dtype='int64', length=100000)
Wall time: 6.05 ms

Int64Index([7141956, 9256789, 1919656, 2407372, 9181191, 2474961, 2345700,
            4394530, 8864037, 6096638,
            ...
             471501, 3616956, 9397742, 6896140,  670892, 9546169, 4146996,
            3465455, 7748682, 5271367],
           dtype='int64', length=100000)

Let's try and use .index after sample to return the indexes of those samples:

sample_dict[user] = series[series==user].sample(n=sample_size, replace=False).index

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pandas.pydata.org › pandas-docs › stable › generated › pandas.Series.sample.html

pandas.Series.sample — pandas 2.2.2 documentation

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pandas.pydata.org › pandas-docs › version › 0.24.0rc1 › api › generated › pandas.Series.sample.html

pandas.Series.sample — pandas 0.24.0rc1 documentation

Generates a random sample from a given 1-D numpy array. ... >>> df = pd.DataFrame({'num_legs': [2, 4, 8, 0], ... 'num_wings': [2, 0, 0, 0], ... 'num_specimen_seen': [10, 2, 1, 8]}, ... index=['falcon', 'dog', 'spider', 'fish']) >>> df num_legs num_wings num_specimen_seen falcon 2 2 10 dog 4 ...

pandas.pydata.org › pandas-docs › version › 2.2.1 › reference › api › pandas.Series.sample.html

pandas.Series.sample — pandas 2.2.1 documentation

Generates random samples from each group of a Series object.

pandas.pydata.org › docs › dev › reference › api › pandas.Series.sample.html

pandas.Series.sample — pandas 3.1.0.dev0+1159.gd7b577e035 documentation

Extract 3 random elements from the Series df['num_legs']: Note that we use random_state to ensure the reproducibility of the examples. >>> df["num_legs"].sample(n=3, random_state=1) fish 0 spider 8 falcon 2 Name: num_legs, dtype: int64

spark.apache.org › docs › latest › api › python › reference › pyspark.pandas › api › pyspark.pandas.Series.sample.html

pyspark.pandas.Series.sample — PySpark 4.1.1 documentation

Return a random sample of items from an axis of object. Please call this function using named argument by specifying the frac argument. You can use random_state for reproducibility. However, note that different from pandas, specifying a seed in pandas-on-Spark/Spark does not guarantee the sampled ...

w3resource.com › python-exercises › pandas › index-data-series.php

Pandas Data Series: Exercises, Practice, Solution

Write a Pandas program to add, subtract, multiple and divide two Pandas Series. Sample Series: [2, 4, 6, 8, 10], [1, 3, 5, 7, 9] Click me to see the sample solution

w3resource.com › pandas › series › pandas-series-sample.html

pandas-series-sample

import numpy as np import pandas as pd · In [2]: df = pd.DataFrame({'num_legs': [2, 4, 8, 0], 'num_wings': [2, 0, 0, 0], 'num_specimen_seen': [8, 2, 1, 6]}, index=['sparrow', 'cat', 'spider', 'snake']) df · Out[2]: Extract 3 random elements from the Series df['num_legs']: Note that we use ...

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pandas: Random sampling from DataFrame with sample() | note.nkmk.me

May 22, 2022 - You can get a random sample from pandas.DataFrame and Series by the sample() method. This is useful for checking data in a large pandas.DataFrame, Series. pandas.DataFrame.sample — pandas 1.4.2 docum ...

Spark By {Examples}

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Pandas Series Tutorial with Examples - Spark By {Examples}

June 19, 2025 - Pandas Series Introduction This is a beginner’s guide of Python pandas Series Tutorial where you will learn what is pandas Series? its features,

Spark By {Examples}

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Pandas Series sample() Function - Spark By {Examples}

July 31, 2024 - In Pandas, the sample() function is used to obtain a random sample of items from a Pandas Series. It allows you to specify the number of items

Towards Data Science

towardsdatascience.com › home › latest › 20 examples to master pandas series

20 Examples to Master Pandas Series | Towards Data Science

January 29, 2025 - It returns the Series with boolean values indicating missing values with True. ... We can count the number of missing values by chaining the sum function with the isna function. ... In data analysis, we are most likely to have numerical values. Pandas is highly capable of manipulating numerical data.

api-docs.databricks.com › python › pyspark › latest › pyspark.pandas › api › pyspark.pandas.Series.sample.html

pyspark.pandas.Series.sample — PySpark master documentation

Series.sample(n: Optional[int] = None, frac: Optional[float] = None, replace: bool = False, random_state: Optional[int] = None, ignore_index: bool = False) → pyspark.pandas.series.Series¶