All Questions
Tagged with statistics dataframe
435
questions
0
votes
1
answer
22
views
Running multiple ICCs on one dataframe in R
I'm trying to calculate multiple ICCs from a data frame created in R. The data frame contains over 2500 observations from 122 different persons. I need an ICC calculated for each person.
Creating a ...
0
votes
0
answers
17
views
Multi variant regression analysis for non-continuous data attributes using Python
Hi wondering if anyone can recommend an approach to carrying out regression analysis..
I am trying to understand the interaction between a set of non-continuous variables (i.e. TRUE/FALSE etc.) on a ...
- 1
-1
votes
1
answer
50
views
Statistical Analysis of antibiograms
I'm currently working on a dataset obtained from different antibiograms tests of different people. My aim is to propose a model to predict and study sensibility/resistance of atibiotics. I'll attach ...
0
votes
0
answers
104
views
How to define EC50 and R squares?
I have a data set as df:
df <- data.frame(
Cases = rep(c("A", "B"), each = 8),
X = c(555.00, 138.75, 34.69, 8.67, 2.17, 0.54, 0.14, 0.03,
555.00, 138.75, 34.69, 8.67, 2.17,...
- 765
1
vote
1
answer
62
views
How can I calculate the difference between two named columns in a huge CSV file, then save the results to a second CSV file?
I have a CSV file containing almost 200 million rows (gigabytes of data). It has only 5 columns. I want to iterate over the data and do simple calculations, first between columns, but then between ...
- 1,436
1
vote
2
answers
57
views
How to replace dataframe values based on index statistics
I have a dataframe like this:
l1 = [1,2,3,4,5,6,7,8,9,10]
l2 = [11,12,13,14,15,16,17,18,19,20]
index = ['FORD','GM']
df = pd.DataFrame(l1,l2).reset_index().T
df.index = index
I want to replace these ...
- 337
0
votes
0
answers
25
views
dplyr summarise function rounding the means [duplicate]
I have this MRE data frame in R:
set.seed(42)
height <- runif(12, min = 6, max = 18)
line <- rep(1:2, each = 6)
treatment <- rep(1:2, times = 6)
block <- ...
0
votes
0
answers
51
views
Python + Excel - deriving a correlated mean from 2 data groups?
What I'm doing - I have two columns in Excel: price and borough(British for district). I've generated the overall data set using python too, so I already have a list composed of the various boroughs. ...
- 13
0
votes
0
answers
36
views
Cannot perform repeated measures ANOVA in R
Consider this data frame:
> pdf
# A tibble: 80 × 9
Subject SessionType Group ErrsOfCom ErrsOfOm TotalErrors Acc AvgRT
<fct> <fct> <fct> <int> <int&...
- 326
0
votes
1
answer
81
views
pandas cut function's output is not understandable
ı want create frequency table with pandas ı tried this code but ı dont understand output also ı want change class range
data:
Rank
1 18.42
2 20.93
3 31.50
4 23.99
5 5.65
...
0
votes
1
answer
81
views
How do I create a Python Lambda lambda function to do this?
I have a dataframe which has a mean and standard deviation and I want to create a lambda function, or some other method, to contain the 1% Value at Risk level. The function for a scalar for what I ...
- 49
0
votes
0
answers
31
views
Having troubles with the subset function in R [duplicate]
I have finished to write a shiny app, the problem is that when I run it certain combinations of plots between different element of the column "country" of the data.frame aren't shown. I ...
- 1
0
votes
1
answer
61
views
Why does pd.cut produce NaN values
Why does pd.cut produce NaN values ?
Input
s = pd.Series(np.arange(6))
df = pd.DataFrame({'Bin': pd.cut(s, [105, 110, 115, 120, 125, 130]),
'Frequency': [2,5,6,8,8,1]})
df
Output
...
- 91
0
votes
2
answers
68
views
How to use !!sym when performing a shapiro_test on a dataframe undergoing a for loop?
I am trying to loop through a dataframe and run both statistical summaries, tests and graph a plot by looping through certain columns within the dataframe. I am new to for loops in r, and sort of ...
- 19
0
votes
5
answers
444
views
Column-wise input nature of a dataframe
I am curious why the default way to pass data to a dataframe is column-based, rather than row-based. For example, something like:
d = {'name': ['John', 'Peter'], 'age': [10, 20]}
df = pd.DataFrame(...
- 108k