dataframe sample python - Brave Search

Random Sample of a subset of a dataframe in Pandas

stackoverflow.com › questions › 38085547 › random-sample-of-a-subset-of-a-dataframe-in-pandas

You can use the sample method*:

In [11]: df = pd.DataFrame([[1, 2], [3, 4], [5, 6], [7, 8]], columns=["A", "B"])

In [12]: df.sample(2)
Out[12]:
   A  B
0  1  2
2  5  6

In [13]: df.sample(2)
Out[13]:
   A  B
3  7  8
0  1  2

*On one of the section DataFrames.

Note: If you have a larger sample size that the size of the DataFrame this will raise an error unless you sample with replacement.

In [14]: df.sample(5)
ValueError: Cannot take a larger sample than population when 'replace=False'

In [15]: df.sample(5, replace=True)
Out[15]:
   A  B
0  1  2
1  3  4
2  5  6
3  7  8
1  3  4

Answer from Andy Hayden on Stack Overflow

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

pandas.DataFrame.sample — pandas 3.0.5 documentation

>>> df.sample(frac=2, replace=True, random_state=1) num_legs num_wings num_specimen_seen dog 4 0 2 fish 0 0 8 falcon 2 2 10 falcon 2 2 10 fish 0 0 8 dog 4 0 2 fish 0 0 8 dog 4 0 2 · Using a DataFrame column as weights.

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

Pandas Dataframe.sample() | Python - GeeksforGeeks

July 11, 2025 - The sample(n=1) function selects one random row from the DataFrame.

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w3schools.com › python › pandas › ref_df_sample.asp

Pandas DataFrame sample() Method

A DataFrame with a sample of the original DataFrame. ... If you want to use W3Schools services as an educational institution, team or enterprise, send us an e-mail: sales@w3schools.com · If you want to report an error, or if you want to make a suggestion, send us an e-mail: help@w3schools.com · HTML Tutorial CSS Tutorial JavaScript Tutorial How To Tutorial SQL Tutorial Python ...

docs.vultr.com › python › third-party › pandas › DataFrame › sample

Python Pandas DataFrame sample() - Random Row or Column Selection | Vultr Docs

December 24, 2024 - Since the original DataFrame has 4 rows, it returns 2 rows randomly. For reproducible results, use the random_state parameter. Pass an integer to random_state which acts as the seed for the random number generator. ... # Sampling with a seed for reproducibility sample_seed = df.sample(n=2, random_state=1) print(sample_seed) Explain Code

stackoverflow.com › questions › 38085547 › random-sample-of-a-subset-of-a-dataframe-in-pandas

python - Random Sample of a subset of a dataframe in Pandas - Stack Overflow

You can use the sample method*:

In [11]: df = pd.DataFrame([[1, 2], [3, 4], [5, 6], [7, 8]], columns=["A", "B"])

In [12]: df.sample(2)
Out[12]:
   A  B
0  1  2
2  5  6

In [13]: df.sample(2)
Out[13]:
   A  B
3  7  8
0  1  2

*On one of the section DataFrames.

Note: If you have a larger sample size that the size of the DataFrame this will raise an error unless you sample with replacement.

In [14]: df.sample(5)
ValueError: Cannot take a larger sample than population when 'replace=False'

In [15]: df.sample(5, replace=True)
Out[15]:
   A  B
0  1  2
1  3  4
2  5  6
3  7  8
1  3  4

One solution is to use the choice function from numpy.

Say you want 50 entries out of 100, you can use:

import numpy as np
chosen_idx = np.random.choice(1000, replace=False, size=50)
df_trimmed = df.iloc[chosen_idx]

This is of course not considering your block structure. If you want a 50 item sample from block i for example, you can do:

import numpy as np
block_start_idx = 1000 * i
chosen_idx = np.random.choice(1000, replace=False, size=50)
df_trimmed_from_block_i = df.iloc[block_start_idx + chosen_idx]

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

pyspark.pandas.DataFrame.sample — PySpark 4.1.2 documentation

A new object of same type as caller containing the sampled items. ... >>> df = ps.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'], ...

medium.com › data-science › how-to-sample-a-dataframe-in-python-pandas-d18a3187139b

How to Sample a Dataframe in Python Pandas | by Angelica Lo Duca | TDS Archive | Medium

July 7, 2021 - Given a dataframe with N rows, random Sampling extract X random rows from the dataframe, with X ≤ N. Python pandas provides a function, named sample() to perform random sampling.

note.nkmk.me › home › python › pandas

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

May 22, 2022 - pandas: Reset index of DataFrame, Series with reset_index() print(df.sample(n=3).reset_index(drop=True)) # sepal_length sepal_width petal_length petal_width species # 0 4.9 3.1 1.5 0.2 setosa # 1 7.9 3.8 6.4 2.0 virginica # 2 6.3 2.8 5.1 1.5 virginica · source: pandas_sample.py · Python ·

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

Pandas DataFrame: - sample() function - w3resource

August 19, 2022 - The sample() function is used to get a random sample of items from an axis of object. ... DataFrame.sample(self, n=None, frac=None, replace=False, weights=None, random_state=None, axis=None)

pandas.pydata.org › pandas-docs › version › 1.5 › reference › api › pandas.DataFrame.sample.html

pandas.DataFrame.sample — pandas 1.5.3 documentation

>>> df.sample(frac=2, replace=True, random_state=1) num_legs num_wings num_specimen_seen dog 4 0 2 fish 0 0 8 falcon 2 2 10 falcon 2 2 10 fish 0 0 8 dog 4 0 2 fish 0 0 8 dog 4 0 2 · Using a DataFrame column as weights.

pandas.pydata.org › pandas-docs › version › 0.22.0 › generated › pandas.DataFrame.sample.html

pandas.DataFrame.sample — pandas 0.22.0 documentation

Returns a random sample of items from an axis of object. ... >>> 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')) >>> df.head() A B C D 0 0.016443 -2.318952 ...

medium.com › @prathik.codes › sampling-dataframes-sample-of-pandas-e94e94b4473b

Sampling DataFrames : sample() of Pandas | by Prathik C | Medium

March 3, 2025 - import pandas as pd import seaborn as sns df = sns.load_dataset('titanic') print(df.info()) # getting the 25% sample of the df rows sample_df_25 = df.sample(0.25) print(sample_df_25.info()) # getting sample of 2 columns from df sample_df_2 = df.sample(2,axis=1) print(sample_df_2.info()) ... # df.info <class 'pandas.core.frame.DataFrame'> RangeIndex: 891 entries, 0 to 890 Data columns (total 15 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 survived 891 non-null int64 1 pclass 891 non-null int64 2 sex 891 non-null object 3 age 714 non-null float64 4 sibsp 891 non-null

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

pandas.DataFrame.sample — pandas 3.1.0.dev0+974.ge652ee88a5 documentation

>>> df.sample(frac=2, replace=True, random_state=1) num_legs num_wings num_specimen_seen dog 4 0 2 fish 0 0 8 falcon 2 2 10 falcon 2 2 10 fish 0 0 8 dog 4 0 2 fish 0 0 8 dog 4 0 2 · Using a DataFrame column as weights.

Machine Learning Plus

machinelearningplus.com › blog › pandas sample – randomly sample rows from dataframe

Pandas Sample - Randomly Sample Rows From Dataframe - machinelearningplus

March 8, 2022 - Use the pandas.DataFrame.sample() method from pandas library to randomly select rows from a Dataframe

pandas.pydata.org › pandas-docs › version › 0.25.0 › reference › api › pandas.DataFrame.sample.html

pandas.DataFrame.sample — pandas 0.25.0 documentation

DataFrame.sample(self, n=None, frac=None, replace=False, weights=None, random_state=None, axis=None)[source]¶

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

pandas.DataFrame.sample — pandas 3.0.4 documentation

>>> df.sample(frac=2, replace=True, random_state=1) num_legs num_wings num_specimen_seen dog 4 0 2 fish 0 0 8 falcon 2 2 10 falcon 2 2 10 fish 0 0 8 dog 4 0 2 fish 0 0 8 dog 4 0 2 · Using a DataFrame column as weights.

programiz.com › python-programming › pandas › methods › sample

Pandas sample()

This is useful when we want to reproduce the same random sample in different runs of your code. Note: The choice of 42 as the seed value is arbitrary; we can use any integer value we like. import pandas as pd # create a DataFrame data = {'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Eve'], 'Age': [25, 32, 28, 22, 30], 'City': ['New York', 'Los Angeles', 'Chicago', 'Houston', 'Miami']} df = pd.DataFrame(data)

spark.apache.org › docs › latest › api › python › reference › pyspark.sql › api › pyspark.sql.DataFrame.sample.html

pyspark.sql.DataFrame.sample — PySpark 4.2.0 documentation

This is not guaranteed to provide exactly the fraction specified of the total count of the given DataFrame. fraction is required and, withReplacement and seed are optional. ... >>> df = spark.range(0, 10, 1, 1) >>> df.sample(0.5, 3).count() 7 >>> df.sample(fraction=0.5, seed=3).count() 4 >>> df.sample(withReplacement=True, fraction=0.5, seed=3).count() 2 >>> df.sample(1.0).count() 10 >>> df.sample(fraction=1.0).count() 10 >>> df.sample(False, fraction=1.0).count() 10

skytowner.com › explore › pandas_dataframe_sample_method

Pandas DataFrame | sample method with Examples

Pandas DataFrame.sample(~) method returns the specified number of rows or columns randomly.

Snowflake Documentation

docs.snowflake.com › en › developer-guide › snowpark › reference › python › 1.17.0 › modin › pandas_api › snowflake.snowpark.modin.pandas.DataFrame.sample

modin.pandas.DataFrame.sample | Snowflake Documentation

>>> 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 0 2 spider 8 0 1 fish 0 0 8 ... >>> df.sample(n=20) num_legs num_wings num_specimen_seen falcon 2 2 10 dog 4 0 2 spider 8 0 1 fish 0 0 8