statistics

How ignore specific range of rows in a dataframe

How ignore specific range of rows in a dataframe Question: I have a dataframe with 1000000 rows and I want to ignore 8000 rows in first 40000 rows and then ignore 80000 rows in next 40000 rows. How can I achieve this ? As an example: Drop 1 to 8000, 40001 to 48000, 80001 to …

Total answers: 1

How to plot perform linear regression analysis on a simple data set

How to plot perform linear regression analysis on a simple data set Question: I am writing a simple Python program to analyze a data set using linear regression. The program is constructed like so # Author: Evan Gertis # Date 11/15 # program: linear regression import pandas as pd import seaborn as sns import matplotlib.pyplot …

Total answers: 1

Python List Statistics not correct

Python List Statistics not correct Question: I try to calculate some stats for a list. But somehow these are not correct: Code: import pandas as pd import statistics list_runs_stats=[4.149432, 3.133142, 3.182976, 2.620959, 3.200038, 2.66668, 2.604444, 2.683382, 3.249564, 3.149947] list_stats=pd.Series(list_runs_stats).describe() print (list_stats.mean()) print (list_stats.min()) print (list_stats.max()) print (list_stats.median()) print (list_stats.count()) Result: 3.6617099664905832 0.467574831924664 10.0 3.10280045 8 …

Total answers: 3

How do I take the average (mean) of inputted numbers in Python?

How do I take the average (mean) of inputted numbers in Python? Question: I would like to take create a code that takes an input of numbers, and then takes the average (mean) of these numbers. So far, I have this: from statistics import mean numbers=int(input("Enter some numbers. Seperate each number by a space: ") …

Total answers: 4

Why am I getting multiple curves instead of one in a pdf

Why am I getting multiple curves instead of one in a pdf Question: I’m trying to plot a histogram and a pdf for a normal distribution function of data_2, but I’m getting multiple lines instead of one, like this Here is my code def normal_dist(data_list): density_func = sps.norm.pdf(data_list, np.mean(data_list), np.std(data_list)) return density_func def plot_histo(data_list, bin_count …

Total answers: 1

Trying to generate a conditional coin flip

Trying to generate a conditional coin flip Question: So I’m a trying to create a function which first flips an unbiased coin but if the result is heads it flips a biased coin with 0.75 probability of heads. If it shows tails then the next flip is unbiased. I’ve tried the following code but I …

Total answers: 3

Randomness Functions Succeeds on the first try most often in Python; why?

Randomness Functions Succeeds on the first try most often in Python; why? Question: I’m running some code to figure out the probability of an event happening on the first attempt, on the second attempt, etc. The problem I’m facing doesn’t have to do with the code itself, but rather the random library, I believe. import …

Total answers: 2

aggregate statistic on pyspark columns, handling nulls

aggregate statistic on pyspark columns, handling nulls Question: I have a trivial question regarding the aggregate statistic on sparkpyspark I was not able to find an answer here on stack overflow, neither on the doc Assuming a column like this one: |COL | |null | |null | |null | |14.150919 | |1.278803 | |null | …

Total answers: 1

Pandas sum of count per percentile of rows

Pandas sum of count per percentile of rows Question: Here is a link to a working example on Google Colaboratory. I have a dataset that represents the reviews (between 0.0 to 10.0) that users have left on various books. It looks like this: user sum count mean 0 2 0.0 1 0.000000 60223 159665 8.0 …

Total answers: 1

How to estimate confidence-intervals beyond the current simulated step, based on existing data for 1,000,000 monte-carlo simulations?

How to estimate confidence-intervals beyond the current simulated step, based on existing data for 1,000,000 monte-carlo simulations? Question: Situation: I have a program which generates 600 random numbers per "step". These 600 numbers are fed into a complicated algorithm, which then outputs a single value (which can be positive or negative) for that "step"; let’s …

Total answers: 1