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I followed the example code and have the following elements in the code. However, I keep getting the error I posted below with traceback from the line for tukey_hsd function.
It keeps returning a TypeError: Could not convert ['AAAAA'] to numeric.
For some reason it is returning the column name in the amount of times there are variables and I'm unsure what the problem is. I specifically tried using the example code only to see if I missed something in my version of the code but it also throws the same error. I've provided both the code and the error traceback and hope @reneshbedre you can help with this! Your code and tutorial have otherwise been amazing and super helpful. Thank you!
from bioinfokit.analys import stat
res = stat()
res.tukey_hsd(df=df_melt, res_var='value', xfac_var='treatments', anova_model='value ~ C(treatments)')
res.tukey_summary
Traceback (most recent call last):
res.tukey_hsd(df=df_melt, res_var='value', xfac_var='treatments', anova_model='value ~ C(treatments)')
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/bioinfokit/analys.py", line 882, in tukey_hsd
mult_group, mult_group_count, sample_size_r = analys_general.get_list_from_df(df, xfac_var, res_var, 'get_dict')
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/bioinfokit/analys.py", line 421, in get_list_from_df
mult_group[ele] = df[df[xfac_var] == ele].mean().loc[res_var]
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/frame.py", line 11335, in mean
result = super().mean(axis, skipna, numeric_only, **kwargs)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/generic.py", line 11984, in mean
return self._stat_function(
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/generic.py", line 11941, in _stat_function
return self._reduce(
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/frame.py", line 11204, in _reduce
res = df._mgr.reduce(blk_func)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/internals/managers.py", line 1459, in reduce
nbs = blk.reduce(func)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/internals/blocks.py", line 377, in reduce
result = func(self.values)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/frame.py", line 11136, in blk_func
return op(values, axis=axis, skipna=skipna, **kwds)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/nanops.py", line 147, in f
result = alt(values, axis=axis, skipna=skipna, **kwds)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/nanops.py", line 404, in new_func
result = func(values, axis=axis, skipna=skipna, mask=mask, **kwargs)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/nanops.py", line 720, in nanmean
the_sum = _ensure_numeric(the_sum)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/nanops.py", line 1678, in _ensure_numeric
raise TypeError(f"Could not convert {x} to numeric")
TypeError: Could not convert ['AAAAA'] to numeric
The text was updated successfully, but these errors were encountered:
Hello!
I followed the example code and have the following elements in the code. However, I keep getting the error I posted below with traceback from the line for tukey_hsd function.
It keeps returning a TypeError: Could not convert ['AAAAA'] to numeric.
For some reason it is returning the column name in the amount of times there are variables and I'm unsure what the problem is. I specifically tried using the example code only to see if I missed something in my version of the code but it also throws the same error. I've provided both the code and the error traceback and hope @reneshbedre you can help with this! Your code and tutorial have otherwise been amazing and super helpful. Thank you!
import pandas as pd
df = pd.read_csv("https://reneshbedre.github.io/assets/posts/anova/onewayanova.txt", sep="\t")
df_melt = pd.melt(df.reset_index(), id_vars=['index'], value_vars=['A', 'B', 'C', 'D'])
df_melt.columns = ['index', 'treatments', 'value']
from bioinfokit.analys import stat
res = stat()
res.tukey_hsd(df=df_melt, res_var='value', xfac_var='treatments', anova_model='value ~ C(treatments)')
res.tukey_summary
Traceback (most recent call last):
res.tukey_hsd(df=df_melt, res_var='value', xfac_var='treatments', anova_model='value ~ C(treatments)')
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/bioinfokit/analys.py", line 882, in tukey_hsd
mult_group, mult_group_count, sample_size_r = analys_general.get_list_from_df(df, xfac_var, res_var, 'get_dict')
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/bioinfokit/analys.py", line 421, in get_list_from_df
mult_group[ele] = df[df[xfac_var] == ele].mean().loc[res_var]
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/frame.py", line 11335, in mean
result = super().mean(axis, skipna, numeric_only, **kwargs)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/generic.py", line 11984, in mean
return self._stat_function(
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/generic.py", line 11941, in _stat_function
return self._reduce(
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/frame.py", line 11204, in _reduce
res = df._mgr.reduce(blk_func)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/internals/managers.py", line 1459, in reduce
nbs = blk.reduce(func)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/internals/blocks.py", line 377, in reduce
result = func(self.values)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/frame.py", line 11136, in blk_func
return op(values, axis=axis, skipna=skipna, **kwds)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/nanops.py", line 147, in f
result = alt(values, axis=axis, skipna=skipna, **kwds)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/nanops.py", line 404, in new_func
result = func(values, axis=axis, skipna=skipna, mask=mask, **kwargs)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/nanops.py", line 720, in nanmean
the_sum = _ensure_numeric(the_sum)
File "/Users/Irene/Library/Python/3.9/lib/python/site-packages/pandas/core/nanops.py", line 1678, in _ensure_numeric
raise TypeError(f"Could not convert {x} to numeric")
TypeError: Could not convert ['AAAAA'] to numeric
The text was updated successfully, but these errors were encountered: