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How to create a dictionary of permutation values？

I need to assign 0 and 1 as values to keys in the dictionaries:
combinations_string_list = [num_list_to_str(i) for i in itertools.product([0, 1], repeat=2)]
all_stategy = []
for i in range(16):
strategy_table = {x: y for x in combinations_string_list for y in [0, 1]}
all_stategy.append(strategy_table)
print(all_stategy)
I got [{'00': 1, '01': 1, '10': 1, '11': 1}, {'00': 1, '01': 1, '10': 1, '11': 1}, {'00': 1, '01': 1, '10': 1, '11': 1}, ...]
but I need [{'00': 0, '01': 0, '10': 0, '11': 0}, {'00': 0, '01': 0, '10': 0, '11': 1}, {'00': 0, '01': 0, '10': 1, '11': 0}, ...] instead.
How can I create this kind of value? Thanks!

You can zip the key sequence ["0", "1"] with each element of the cartesian product to produce input to dict:
>>> [dict(zip(["0", "1"], x)) for x in product([0,1], repeat=2)]
[{'0': 0, '1': 0}, {'0': 0, '1': 1}, {'0': 1, '1': 0}, {'0': 1, '1': 1}]
or
>>> values=[0,1]
>>> [dict(zip(map(str, values), x)) for x in product(values, repeat=2)]

Printing possible substring in set of 3 and matching with dictionary keys in python

I want to print possible substring in set of 3 and assign dictionary values if pattern matches with dictionary.keys() and store them into new dictionary
input:
dict1={'000': 0, '001': 0, '010': 0, '011': 0, '100': 1, '101': 0, '110': 1, '111': 0}
str1=['010110100']
output:
sub_string= [010,101,011...]
new dict= {'010':0, '101':0, '011':0, '110':1......}

try this:
[str1[0][i:i+3] for i in range(len(str1[0])-2) if str1[0][i:i+3] in dict1]
{str1[0][i:i+3] : dict1.get(str1[0][i:i+3]) for i in range(len(str1[0])-2) if str1[0][i:i+3] in dict1}
# ['010', '101', '011', '110', '101', '010', '100']
# {'010': 0, '101': 0, '011': 0, '110': 1, '100': 1}

You could do like this:
dict1={'000': 0, '001': 0, '010': 0, '011': 0, '100': 1, '101': 0, '110': 1, '111': 0}
str1= '010110100'
sub_string = []
d = {}
for i in range(len(str1)-2):
temp = str1[i:i+3]
sub_string.append(temp)
d[temp] = dict1.get(temp)
print(sub_string)
print(d)
['010', '101', '011', '110', '101', '010', '100']
{'010': 0, '101': 0, '011': 0, '110': 1, '100': 1}

Pandas - Add a column level to multi index

I would like to add a sublevel (L4) in my dataframe, based on a list of values:
x = [0.01, 0.01, 0.01, 0.02, 0.02, 0.02]
The df.columns returns me this:
MultiIndex(levels=[['Foo', 'Bar'], ['A', 'B', 'C'], ['a']],
labels=[[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2], [0, 0, 0, 0, 0, 0]],
names=['L1', 'L2', 'L3'])
So far I have tried that:
df = pd.concat([df], keys=x, names=['L4'], axis=1).swaplevel(i='L4', j='L1', axis=1).swaplevel(i='L4', j='L2', axis=1).swaplevel(i='L4', j='L3', axis=1)
but it doesn't give the good value, it repeats list_levels[0] (0.01).
Do you have any idea on how I can do it ?
Thanks

Here's a way:
cols = pd.MultiIndex(levels=[['Foo', 'Bar'], ['A', 'B', 'C'], ['a']],
labels=[[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2], [0, 0, 0, 0, 0, 0]],
names=['L1', 'L2', 'L3'])
pd.DataFrame(columns = cols).T\
.assign(x = [0.01, 0.01, 0.01, 0.02, 0.02, 0.02])\
.set_index('x', append=True).T
Output:

You can create a DataFrame with the column index as the Index, and the data being the level you want to add, as set_index(append=True) is only defined for the row Index. Then assign it with df.columns = ...
import pandas as pd
idx = pd.MultiIndex(levels=[['Foo', 'Bar'], ['A', 'B', 'C'], ['a']],
codes=[[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2], [0, 0, 0, 0, 0, 0]],
names=['L1', 'L2', 'L3'])
x = [0.01, 0.01, 0.01, 0.02, 0.02, 0.02]
pd.DataFrame(x, index=idx, columns=['L4']).set_index('L4', append=True).index
#MultiIndex([('Foo', 'A', 'a', 0.01),
# ('Foo', 'B', 'a', 0.01),
# ('Foo', 'C', 'a', 0.01),
# ('Bar', 'A', 'a', 0.02),
# ('Bar', 'B', 'a', 0.02),
# ('Bar', 'C', 'a', 0.02)],
# names=['L1', 'L2', 'L3', 'L4'])
Under the hood set_index just recreates the entire MultiIndex when appending, so a more hands-on approach is
arrays = []
for i in range(idx.nlevels):
arrays.append(idx.get_level_values(i))
arrays.append(pd.Index(x, name='L4')) # Add the new level
new_idx = pd.MultiIndex.from_arrays(arrays)
#MultiIndex([('Foo', 'A', 'a', 0.01),
# ('Foo', 'B', 'a', 0.01),
# ('Foo', 'C', 'a', 0.01),
# ('Bar', 'A', 'a', 0.02),
# ('Bar', 'B', 'a', 0.02),
# ('Bar', 'C', 'a', 0.02)],
# names=['L1', 'L2', 'L3', 'L4'])

Replicate a nested for-loop with a dict-comprehension

Given the following code:
minimal example of list of lists:
c = [['dog', 'Sg', 'Good'], ['cat', 'Pl', 'Okay'], ['dog', 'Pl', 'Bad'],
['dog', 'Sg', 'Good'], ['cat', 'Pl', 'Okay'], ['dog', 'Pl', 'Okay'],
['dog', 'Sg', 'Good'], ['cat', 'Sg', 'Good'], ['dog', 'Pl', 'Bad'],
['dog', 'Sg', 'Good'], ['cat', 'Pl', 'Okay'], ['dog', 'Pl', 'Bad']]
create sets of words from c
outer_keys = set()
inner_keys = set()
for x in c:
outer_keys.add(x[0])
inner_keys |= set(x[1:])
create dict with for loop
Lemma = dict()
for i in outer_keys:
j_d = dict()
for j in inner_keys:
j_d[j] = 0
j_d[i] = 0 # this is the line I can't replicate with a comprehension
Lemma[i] = j_d
for loop result:
{'dog': {'Okay': 0, 'Pl': 0, 'Good': 0, 'Bad': 0, 'Sg': 0, 'dog': 0},
'cat': {'Okay': 0, 'Pl': 0, 'Good': 0, 'Bad': 0, 'Sg': 0, 'cat': 0}}
using dict comprehension:
This is where I need assistance. I haven't been able to replicate the for-loop with the dict comprehension
Lemma = {j: {i: 0 for i in inner_keys} for j in outer_keys}
Note: dog should be inside the value of outer dog and the same for cat
My dict comprehension result:
{'dog': {'Okay': 0, 'Pl': 0, 'Good': 0, 'Bad': 0, 'Sg': 0},
'cat': {'Okay': 0, 'Pl': 0, 'Good': 0, 'Bad': 0, 'Sg': 0}}
Question:
How can I replicate the result of the for-loop with the dict comprehension?
Order doesn't matter.

You can use dict.fromkeys together with inner_keys | {j}:
>>> {j: dict.fromkeys(inner_keys | {j}, 0) for j in outer_keys}
{'cat': {'Bad': 0, 'Good': 0, 'Okay': 0, 'Pl': 0, 'Sg': 0, 'cat': 0},
'dog': {'Bad': 0, 'Good': 0, 'Okay': 0, 'Pl': 0, 'Sg': 0, 'dog': 0}}

Just create a new dict from your inner dict
>>> {j: dict({i: 0 for i in inner_keys}, **{j:0}) for j in outer_keys}
{'dog': {'Bad': 0, 'Good': 0, 'Okay': 0, 'Sg': 0, 'dog': 0, 'Pl': 0}, 'cat': {'Bad': 0, 'Good': 0, 'Okay': 0, 'Sg': 0, 'Pl': 0, 'cat': 0}}

Class constant dictionary in Python

I'm building a module that has a class variable dictionary:
class CodonUsageTable:
CODON_DICT={'TTT': 0, 'TTC': 0, 'TTA': 0, 'TTG': 0, 'CTT': 0,
'CTC': 0, 'CTA': 0, 'CTG': 0, 'ATT': 0, 'ATC': 0,
'ATA': 0, 'ATG': 0, 'GTT': 0, 'GTC': 0, 'GTA': 0,
'GTG': 0, 'TAT': 0, 'TAC': 0, 'TAA': 0, 'TAG': 0,
'CAT': 0, 'CAC': 0, 'CAA': 0, 'CAG': 0, 'AAT': 0,
'AAC': 0, 'AAA': 0, 'AAG': 0, 'GAT': 0, 'GAC': 0,
'GAA': 0, 'GAG': 0, 'TCT': 0, 'TCC': 0, 'TCA': 0,
'TCG': 0, 'CCT': 0, 'CCC': 0, 'CCA': 0, 'CCG': 0,
'ACT': 0, 'ACC': 0, 'ACA': 0, 'ACG': 0, 'GCT': 0,
'GCC': 0, 'GCA': 0, 'GCG': 0, 'TGT': 0, 'TGC': 0,
'TGA': 0, 'TGG': 0, 'CGT': 0, 'CGC': 0, 'CGA': 0,
'CGG': 0, 'AGT': 0, 'AGC': 0, 'AGA': 0, 'AGG': 0,
#Other code
def __init__(self,seqobj):
'''Creates codon table for a given Bio.seq object.i
The only argument is Bio.Seq object with DNA
Currently assumes seq to be DNA, RNA support to be added later'''
dnaseq=str(seqobj)
self.usage_table=CodonUsageTable.CODON_DICT.deepcopy()#instance of table
The last line must make a copy of class dictionary to store instance data in it, but it throws
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "./codon_usage.py", line 47, in __init__
self.usage_table=CodonUsageTable.CODON_DICT.deepcopy()#instance of codon usage table
NameError: global name 'CODON_DICT' is not defined
So does self.CODON_DICT, CODON_DICT or codon_usage.CodonUsageTable.CODON_DICT, when called from __init__. Dictionary is defined:
>>>import codon_usage
>>> codon_usage.CodonUsageTable.CODON_DICT
{'GCT': 0, 'GGA': 0, 'TTA': 0, 'GAT': 0, 'TTC': 0, 'TTG': 0, 'AGT': 0, 'GCG': 0, 'AGG': 0, 'GCC': 0, 'CGA': 0, 'GCA': 0, 'GGC': 0, 'GAG': 0, 'GAA': 0, 'TTT': 0, 'GAC': 0, 'TAT': 0, 'CGC': 0, 'TGT': 0, 'TCA': 0, 'GGG': 0, 'TCC': 0, 'ACG': 0, 'TCG': 0, 'TAG': 0, 'TAC': 0, 'TAA': 0, 'ACA': 0, 'TGG': 0, 'TCT': 0, 'TGA': 0, 'TGC': 0, 'CTG': 0, 'CTC': 0, 'CTA': 0, 'ATG': 0, 'ATA': 0, 'ATC': 0, 'AGA': 0, 'CTT': 0, 'ATT': 0, 'GGT': 0, 'AGC': 0, 'ACT': 0, 'CGT': 0, 'GTT': 0, 'CCT': 0, 'AAG': 0, 'CGG': 0, 'AAC': 0, 'CAT': 0, 'AAA': 0, 'CCC': 0, 'GTC': 0, 'CCA': 0, 'GTA': 0, 'CCG': 0, 'GTG': 0, 'ACC': 0, 'CAA': 0, 'CAC': 0, 'AAT': 0, 'CAG': 0} 'GGT': 0, 'GGC': 0, 'GGA': 0, 'GGG': 0}

The symptoms imply that the story went like this:
you wrote the file and saved it;
you ran the Python shell;
you found that CODON_DICT can't be accessed just like that and fixed that;
you tried that call again within the same Python shell and got that error.
That happens because Python is still using the old version of the module, which is loaded during the import. Although it shows the line from the new file, since all it has in the memory is the bytecode with metadata and has to refer to the disk when error happens. If you want to pick your latest changes without restarting the shell, run:
>>> reload(codon_usage)
and try again.
(A sidenote: dict has no method deepcopy, that function comes from the module copy. dict.copy is enough here, though).