Develop Reference

How to standardize address type properly

I'm trying to standardize street address by converting the abbreviations to the full word (e.g. RD - Road). I created many lines to account for different spellings and ran into an issue where one replace code overrode another one
import pandas as pd
mydata = {'Street_type': ['PL', 'pl', 'Pl', 'PLACE', 'place']}
mydata = pd.DataFrame(mydata)
mydata['Street_type'] = mydata['Street_type'].replace('PL','Place',regex=True)
mydata['Street_type'] = mydata['Street_type'].replace('pl','Place',regex=True)
mydata['Street_type'] = mydata['Street_type'].replace('Pl','Place',regex=True)
mydata['Street_type'] = mydata['Street_type'].replace('PLACE','Place',regex=True)
mydata['Street_type'] = mydata['Street_type'].replace('place','Place',regex=True)
Instead of Place, I got Placeace. What is the best way to avoid this error? Do I write a if-else statement or any function? Thanks in advance!

Among other problems, you have overlapping logic: you fail to check that the target ("old") string is a full word before you replace it. For instance, with the input type of "PLACE", you trigger both the first and third replacements, generating PlaceACE and then PlaceaceACE before you get to the condition you wanted.
You need to work through your tracking and exclusion logic carefully, and then apply only one of the replacements. You can check the length of the street_type and apply the unique transition you need for that length.
If you're trying to convert a case statement, then you need to follow that logic pattern, rather than the successive applications you coded. You can easily look up how to simulate a "case" statement in Python.
Also consider using a translation dictionary, such as
type_trans = {
"pl": "Place",
"Pl": "Place",
"PLACE": "Place",
...
}
Then your change is simply
mydata['Street_type'] = type_trans[mydata['Street_type']]
Also, you might list all of the variants in a tuple, such as:
type_place = ("PL", "Pl", "pl", "PLACE", "place")
if mydata['Street_type'] in type_place
mydata['Street_type'] = "Place"
... but be sure to generalize this properly for your entire list of street types.

You can do this correctly with a single pass if you use a proper regex here, e.g. use word boundaries (\b):
In [11]: places = ["PL", "pl", "Pl", "PLACE", "Place", "place"]
In [12]: mydata.Street_type
Out[12]:
0 PL
1 pl
2 Pl
3 PLACE
4 place
Name: Street_type, dtype: object
In [13]: mydata.Street_type.replace("(^|\b)({})(\b|$)".format("|".join(places)), "Place", regex=True)
Out[13]:
0 Place
1 Place
2 Place
3 Place
4 Place
Name: Street_type, dtype: object

#Needlemanwunch
def zeros(shape):
retval = []
for x in range(shape[0]):
retval.append([])
for y in range(shape[1]):
retval[-1].append(0)
return retval
match_award = 10
mismatch_penalty = -3
gap_penalty = -4 # both for opening and extanding
def match_score(alpha, beta):
if alpha == beta:
return match_award
elif alpha == '-' or beta == '-':
return gap_penalty
else:
return mismatch_penalty
def finalize(align1, align2):
align1 = align1[::-1] #reverse sequence 1
align2 = align2[::-1] #reverse sequence 2
i,j = 0,0
#calcuate identity, score and aligned sequeces
symbol = ''
found = 0
score = 0
identity = 0
for i in range(0,len(align1)):
# if two AAs are the same, then output the letter
if align1[i] == align2[i]:
symbol = symbol + align1[i]
identity = identity + 1
score += match_score(align1[i], align2[i])
# if they are not identical and none of them is gap
elif align1[i] != align2[i] and align1[i] != '-' and align2[i] != '-':
score += match_score(align1[i], align2[i])
symbol += ' '
found = 0
#if one of them is a gap, output a space
elif align1[i] == '-' or align2[i] == '-':
symbol += ' '
score += gap_penalty
identity = float(identity) / len(align1) * 100
print('Similarity =', "%3.3f" % identity, 'percent')
print('Score =', score)
# print(align1)
# print(symbol)
# print(align2)
def needle(seq1, seq2):
m, n = len(seq1), len(seq2) # length of two sequences
# Generate DP table and traceback path pointer matrix
score = zeros((m+1, n+1)) # the DP table
# Calculate DP table
for i in range(0, m + 1):
score[i][0] = gap_penalty * i
for j in range(0, n + 1):
score[0][j] = gap_penalty * j
for i in range(1, m + 1):
for j in range(1, n + 1):
match = score[i - 1][j - 1] + match_score(seq1[i-1], seq2[j-1])
delete = score[i - 1][j] + gap_penalty
insert = score[i][j - 1] + gap_penalty
score[i][j] = max(match, delete, insert)
# Traceback and compute the alignment
align1, align2 = '', ''
i,j = m,n # start from the bottom right cell
while i > 0 and j > 0: # end toching the top or the left edge
score_current = score[i][j]
score_diagonal = score[i-1][j-1]
score_up = score[i][j-1]
score_left = score[i-1][j]
if score_current == score_diagonal + match_score(seq1[i-1], seq2[j-1]):
align1 += seq1[i-1]
align2 += seq2[j-1]
i -= 1
j -= 1
elif score_current == score_left + gap_penalty:
align1 += seq1[i-1]
align2 += '-'
i -= 1
elif score_current == score_up + gap_penalty:
align1 += '-'
align2 += seq2[j-1]
j -= 1
# Finish tracing up to the top left cell
while i > 0:
align1 += seq1[i-1]
align2 += '-'
i -= 1
while j > 0:
align1 += '-'
align2 += seq2[j-1]
j -= 1
finalize(align1, align2)
needle('kizlerlo','killerpo' )
***********************************************************************************************************************
#import textdistance as txd
import numpy
txd.overlap('kizlerlo','kilerpo' )
txd.jaro('kizlerlo','killerpo' )
txd.cosine('kizlerlo','killerpo' )
#txd.needleman_wunsch('kizlerlo','killerpo' )
txd.jaro_winkler('kizlerlo','killerpo' )
#txd.smith_waterman('Loans and Accounts','Loans Accounts' )
#txd.levenshtein.normalized_similarity('Loans and Accounts','Loans Accounts' )
from scipy.spatial import distance
a = 'kizlerlo'
b = 'kilerpoo'
#txd.gotoh('Loans and Accounts','Loans Accounts' )
print(txd.needleman_wunsch.normalized_similarity('Loans and Accounts','Loans Accounts' ))
***************************************************************************************************************************
#Euclidean
import math
import numpy as np
def euclid(str1,str2):
dist=0.0
x=str1
y=str2
set1=set()
for a in range(0,len(x)):
set1.add(x[a])
for a in range(0,len(y)):
set1.add(y[a])
vec1=[None]*len(set1)
vec2=[None]*len(set1)
for counter,each_char in enumerate(set1):
vec1[counter]=x.count(each_char)
vec2[counter]=y.count(each_char)
dist=1/(1+math.sqrt(sum([(a - b) ** 2 for a, b in zip(vec1, vec2)])))
print(dist)
euclid('kizlerlo','killerpo')
***************************************************************************************************************************
from similarity.qgram import QGram
import affinegap
qgram = QGram(2)
#print(qgram.distance('kizlerlo', 'killerpo'))
affinegap.affineGapDistance('kizlerlokill' ,'erpozlerlzler')
***************************************************************************************************************************
#manhattan
def manhattan(str1,str2):
dist=0.0
x=str1
y=str2
set1=set()
for a in range(0,len(x)):
set1.add(x[a])
for a in range(0,len(y)):
set1.add(y[a])
vec1=[None]*len(set1)
vec2=[None]*len(set1)
for counter,each_char in enumerate(set1):
vec1[counter]=x.count(each_char)
vec2[counter]=y.count(each_char)
#dist= sum([np.abs(a - b) for a, b in zip(vec1, vec2)])
dist=1/(1+sum([np.abs(a - b) for a, b in zip(vec1, vec2)]))
print(dist)
manhattan('kizlerlo','killerpo')
import jellyfish
import json
from Levenshtein import distance,jaro_winkler,jaro,ratio,seqratio
def comp(a,b):
return jellyfish.jaro_winkler(a,b)*100 + distance(a,b) + jaro(a,b)*100
ip = {"CED":"WALMART INC_10958553"}
ala = {}
for index,row in df_ala.iterrows():
a = ip.get("CED")
b = row['NN_UID']
c = comp(a,b)
ala.update({row['N_UID'] : c})
ala_max = max(ala, key=ala.get)
ala_f = {"ALACRA" : ala_max}
ces_f = {"CESIUM" : "WALMART_10958553_CESIUM"}
dun_f = {"DUNS" : "WALMART_10958053_DUNS"}
ref_f = {"REF" : "WALMART INC_10958553_REF"}
cax_f = {"CAX" : "WALMART LTD_10958553_CAX"}
final_op = {**ala_f,**ces_f,**dun_f,**ref_f,**cax_f }
final_json = json.dumps(final_op)
print(final_json)
from flask import Flask,request, jsonify
app = Flask(__name__)
#app.route('/test',methods = ['GET','POST'])
def test():
if request.method == "GET":
return jsonify({"response":"Get request called"})
elif request.method == "POST":
req_Json = request.json
name = req_Json['name']
return jsonify({"response": "Hi" + name})
if __name__ == '__main__':
app.run(debug = True,port = 9090)
{
"name": "Mike"
}
import usaddress
import pandas as pd
import statistics
#sa = dict(usaddress.parse('123 Main St. Suite Chicago, IL' ))
adr = pd.read_excel('C:\\VINAYAK\\Address.xlsx')
adr.columns = ['Address']
strlen = []
scr = []
loop = adr['Address'].tolist()
for i in loop:
strlen.append(len(i))
x = statistics.median(strlen)
for i in loop:
sa = dict(usaddress.parse(i))
sa = list(sa.values())
a = 0
if len(i) > x :
a+= 5
if 'AddressNumber' in sa :
a+= 23
if 'StreetName' in sa :
#a = a + 20
a+= 17
if 'OccupancyType' in sa :
a+= 6
if 'OccupancyIdentifier' in sa :
a+= 12
if 'PlaceName' in sa :
a+= 12
if 'StateName' in sa :
a+= 13
if 'ZipCode' in sa :
a+= 12
scr.append(a)
adr['Adr_Score'] = scr
adr.head()
#(pd.DataFrame([(key) for key in sa.items()])).transpose()
#pd.DataFrame(dict([(value, key) for key, value in sa.items()]))
#pd.DataFrame(dict([(value, key) for key, value in sa.items()]))
# df_ts = pd.DataFrame(columns = ['AddressNumber' , 'Age', 'City' , 'Country'])
# df_ts.append(sa, ignore_index=False, verify_integrity=False, sort=None)
# df_ts.head()
import pandas as pd
from zipfile import ZipFile
# core = []
# f = open('C:/Users/s.natarajakarayalar/1.txt','r')
# core.append(str(f.readlines()))
# print(core)
import os
import zipfile
import re
import nltk
import os
core = []
with zipfile.ZipFile('C:/Users/s.natarajakarayalar/TF.zip') as z:
a = 0
for filename in z.namelist():
#if a < 1:
#if not os.path.isdir(filename):
# read the file
with z.open(filename) as f:
#a = 2
x = f.readlines()
core = core + x
with open('C:/Users/s.natarajakarayalar/fins.txt', 'w') as f:
for item in core:
f.write("%s\n" % item)
# for i in core:
# if k < 5:
# tkt = re.sub(r'.*CONTENT', '', i)
# new_core.append(tkt)
# k = k+1
# for item in core:
# new_core.append(len(item.split()))
# print(sum(new_core))
# from nltk.tokenize import word_tokenize
# new_core = []
# stp = ['URL:https://','TITLE:b','META-KEYWORDS:','None','DOC ID:','CONTENT:b','URL:','TITLE:','META-CONTENT:']
# #new_core = [word for word in core if word not in stopwords]
# for i in core:
# wk = word_tokenize(i)
# for w in wk:
# if w not in stp:
# new_core.append(w)

When i use a for loop with an array it doesn't work and uses the number of items instead of going item by item

Basically in the last for loop the k variable uses the number of items in the list and then I have a false and unique answer rather than multiple answers I want to do some sort of n roots of a complex number (if my question isn't clear sorry i'm not a native english speaker I'll do my best to make it clearer)
from math import *
deg = int(input("entrez le degré:"))
re = int(input("le réel:"))
im = int(input("l'imaginaire:"))
counter = 0
while counter < deg:
counter = counter + 1
kkk = []
kkk.append(counter)
r = sqrt(pow(re,2)+pow(im,2))
if im != 0:
teton = round(pi/radians(degrees(acos(re/r))),1)
else:
teton = round(pi/radians(degrees(acos(im/r))),1)
if round(r) != r:
r = "sqrt(",(pow(re,2)+pow(im,2)),")"
else:
r = r
teta = "pi/%s" %teton
print("z = ",r,"e^i",teta,)
for k in kkk:
if re != 0 or im != 0:
print(r,"e^i*2*",teta,"*",k,"pi")
else:
print(r,"^1/",deg,"e^i(",teta,"/",deg," +(2",k,"pi)/",deg)
print(k)

If I understood the problem correctly, you are saying that for loop is not iterating over all the items in the list kkk.
if you check your code the list kkk always have only one item as you are initializing and appending item in same loop.
please move below statement out of the first loop.
kkk = []
like below.
from math import *
deg = int(input("entrez le degré:"))
re = int(input("le réel:"))
im = int(input("l'imaginaire:"))
counter = 0
kkk = []
while counter < deg:
counter = counter + 1
kkk.append(counter)
r = sqrt(pow(re,2)+pow(im,2))
if im != 0:
teton = round(pi/radians(degrees(acos(re/r))),1)
else:
teton = round(pi/radians(degrees(acos(im/r))),1)
if round(r) != r:
r = "sqrt(",(pow(re,2)+pow(im,2)),")"
else:
r = r
teta = "pi/%s" %teton
print("z = ",r,"e^i",teta,)
for k in kkk:
if re != 0 or im != 0:
print(r,"e^i*2*",teta,"*",k,"pi")
else:
print(r,"^1/",deg,"e^i(",teta,"/",deg," +(2",k,"pi)/",deg)
print(k)

Loop for extracting dictionary values ends prematurely

I'm trying to use this dictionary:
student_data_dict = {'Student_1': 'bbbeaddacddcddaaadbaabdad', 'Student_2': 'acbccaddcadaaacdadbcabcad', 'Student_3': 'babcabdccadcDdbccdbaadbad', 'Student_4': 'bcbcabddcadcdabccdbaadcbd', 'Student_5': 'DCBCCADDCADBDACCDBBACBCAD', 'Student_6': 'acbeccddcadbaaccabbacdcad', 'Student_7': 'BCBCBCDABADCADCCDABAACCAD', 'Student_8': 'dcbccbddcadaabcbcacabbcad', 'Student_9': 'DDBDBBCDDCCBABCCBACADAAAC', 'Student_10': 'cbbdacdacadcbadbabaabcaTa', 'Student_11': 'BDBECADCAADCAAAAACBACACAD', 'Student_12': 'DBBCCBDCCADCDABABCBAABCAD', 'Student_13': 'BCBCBCDDCADCAAACCABACACAD', 'Student_14': 'DBBECBDACADAAACBCBAAABCBD', 'Student_15': 'acbebbddcadbaacccbcaddcad', 'Student_16': 'ACBEBCDDCADBAACCAACADBCAD', 'Student_17': 'DBBCACDDCADCAABCADBABDDAD', 'Student_18': 'dcbcdcdbbddccabbdacacccbd', 'Student_19': 'dbbccbddcadaaaccbdcaaacad', 'Student_20': 'abbdaaddcadcaaccbdcaaccbd', 'Student_21': 'DCDCABDBCADAAACDCCDAACAAD', 'Student_22': 'dabdaddabddbaacdacbaaaaad', 'Student_23': 'BCBCDDDACCDCAABDDABACACAD', 'Student_24': 'ACBDCBDBBCDAACCCCBDAADCBD', 'Student_25': 'DCBCACDAADDCADCBAABACBCAD', 'Student_26': 'dcbaabdccadcdadcccbaabdbd', 'Student_27': 'abbadbddcadacbcacccacbdad'}
and store the first letter for all students as a dictionary entry and then do the same for the next letter ect... to result in:
{'question_1': 'babbDaBdDcBDBDaADddaDdBADda', 'question_2': 'bcacCcCcDbDBCBcCBcbbCaCCCcb', 'question_3': 'bbbbBbBbBbBBBBbBBbbbDbBBBbb', 'question_4': 'ecccCeCcDdECCEeECccdCdCDCaa', 'question_5': 'acaaCcBcBaCCBCbBAdcaAaDCAad', 'question_6': 'dabbAcCbBcABCBbCCcbaBdDBCbb', 'question_7': 'ddddDdDdCdDDDDdDDdddDdDDDdd', 'question_8': 'adcdDdAdDaCCDAdDDbddBaABAcd', 'question_9': 'ccccCcBcDcACCCcCCbccCbCBAcc', 'question_10': 'daaaAaAaCaAAAAaAAdaaAdCCDaa', 'question_11': 'ddddDdDdCdDDDDdDDdddDdDDDdd', 'question_12': 'caccBbCaBcCCCAbBCcacAbCACca', 'question_13': 'daDdDaAaAbADAAaAAcaaAaAAAdc', 'question_14': 'dadaAaDbBaAAAAaAAaaaAaACDab', 'question_15': 'acbbCcCcCdABACcCBbccCcBCCdc', 'question_16': 'adccCcCbCbAACBcCCbccDdDCBca', 'question_17': 'aaccDaDcBaABCCcAAdbbCaDCAcc', 'question_18': 'ddddBbAaAbCCABbADaddCcABAcc', 'question_19': 'bbbbBbBcCaBBBAcCBcccDbBDBbc', 'question_20': 'acaaAaAaAaAAAAaAAaaaAaAAAaa', 'question_21': 'aaaaCcAbDbCACAdDBcaaAaCACac', 'question_22': 'bbddBdCbAcABABdBDcacCaADBbb', 'question_23': 'dcbcCcCcAaCCCCcCDcccAaCCCdd', 'question_24': 'aaabAaAaATAAABaAAbabAaABAba', 'question_25': 'ddddDdDdCaDDDDdDDdddDdDDDdd'}
x = 1
all_letters = ''
letter = ''
y = 1
i = 0
z = 0
for start in student_data_dict:
student = student_data_dict.get('Student_' + str(y))
letter = student[z]
all_letters = all_letters + letter
y = y + 1
i = i + 1
question_data_dict["question " + str(x)] = all_letters
if i == 27:
z = z + 1
x = x + 1
i = 0
print(question_data_dict)
data_file.close()
{'question 1': 'babbDaBdDcBDBDaADddaDdBADda'}
is what I get but I can't get the answers for the other 25 questions.
I tried changing for start in student_data_dict: into while z<26: but at the line "letter = student[z]" I get the error "'NoneType' object is not subscriptable"

num_questions = 25
answers_dict = {}
for i in range(num_questions):
answers_dict['question' + str(i)] = ''.join(c[i] for c in student_data_dict.values())
print(answers_dict)
Will give you the result you want.
Edit
Fixed code. Extracted number of questions to a variable so it can be used as index
Edit2
I created an OrderedDict from your original dictionary to maintain answer order when iterating. Now the answers_dict contains valid data.
from collections import OrderedDict
ordered_data = OrderedDict()
for i in range(len(student_data_dict.items())):
ordered_data['Student_' + str(i + 1)] = student_data_dict.get('Student_' + str(i + 1))
num_questions = 25
answers_dict = {}
for i in range(num_questions):
answers_dict['question' + str(i + 1)] = ''.join(c[i] for c in ordered_data.values())

You need to reset y when you move to the next question.

Here's an alternative a way to get what you're looking for with Pandas:
import pandas as pd
sdd = {k:[x for x in v] for k,v in student_data_dict}
df = pd.DataFrame(sdd)
df = df.reindex_axis(sorted(df.columns,
key = lambda col: int(col.split("_")[-1])), axis=1)
df.index = [f"Question {i+1}" for i in df.index]
{k:''.join(v) for k,v in zip(df.index, df.values)}

How to write program run matrix as below in python?

Thanks for everyone's reply. I will explain here.
Suppose there is a given matrix
x y B = [5,-4,5,-6]
[[0,0,0,0], [[0,1,0,1],
[0,0,0,0], [0,0,0,0],
[0,0,0,0], [0,0,0,1],
[0,0,0,0]] [0,0,0,0]]
for example a feasible solution is [[0,4,0,1],[0,0,0,0],[0,0,0,5],[0,0,0,0]] 4+1-0 == 5 0-4 == -4 5-0 == 5 0 - 5-1 == -6
I want to update x to make sure:
(1) if y[i][j] == 0:
x[i][j] = 0
(2) x[0][0]+x[0][1]+x[0][2]+x[0][3]-x[0][0]-x[1][0]-x[2][0]-x[3][0] = B[0]
x[1][0]+x[1][1]+x[1][2]+x[1][3]-x[0][1]-x[1][1]-x[2][1]-x[3][1] = B[1]
...
How to program to find the feasible x?

answer updated, i wrote some code to parse variables.
B = [5,-4,5,-6]
y = [
[0,1,0,1],
[0,0,0,0],
[0,0,0,1],
[0,0,0,0],
]
x = []
for i, row in enumerate(y):
temp = []
for j, col in enumerate(row):
if col != 0:
temp.append(str(col) + '*x' + str(i) + str(j))
else:
temp.append(col)
x.append(temp)
#for one in x:
# print one
equ = []
for i in xrange(4):
temp1 = []
temp2 = []
for j in xrange(4):
temp1.append(x[i][j])
temp2.append(x[j][i])
temp2.append(B[i])
equ.append(tuple(temp1 + temp2))
equtions = []
for one in equ:
s = '%s + %s + %s + %s - %s - %s - %s - %s = %s' % one
equtions.append(s)
for one in equtions:
print one
import re
from copy import deepcopy
equ_bak = deepcopy(equtions)
p_var = re.compile(r'x\d\d')
vars = set([])
for one in equ_bak:
m = p_var.findall(one)
vars |= set(m)
vars = sorted(list(vars))
p_ef = re.compile(r'([+-]* *\d*)\*(x\d\d)')
effs = []
for one in equ_bak:
m = p_ef.findall(one)
#print m
temp = [0] * len(vars)
for num, var in m:
try:
temp[vars.index(var)] = float(num.replace(' ', ''))
except:
pass
effs.append(tuple(temp))
#for one in effs:
# print one
import numpy as np
A = np.array(effs)
x = np.linalg.lstsq(A,B)
print vars
print x[0]

Why my code is getting NZEC run time error?

Question source: SPOJ.. ORDERS
def swap(ary,idx1,idx2):
tmp = ary[idx1]
ary[idx1] = ary[idx2]
ary[idx2] = tmp
def mkranks(size):
tmp = []
for i in range(1, size + 1):
tmp = tmp + [i]
return tmp
def permutations(ordered, movements):
size = len(ordered)
for i in range(1, size): # The leftmost one never moves
for j in range(0, int(movements[i])):
swap(ordered, i-j, i-j-1)
return ordered
numberofcases = input()
for i in range(0, numberofcases):
sizeofcase = input()
tmp = raw_input()
movements = ""
for i in range(0, len(tmp)):
if i % 2 != 1:
movements = movements + tmp[i]
ordered = mkranks(sizeofcase)
ordered = permutations(ordered, movements)
output = ""
for i in range(0, sizeofcase - 1):
output = output + str(ordered[i]) + " "
output = output + str(ordered[sizeofcase - 1])
print output

Having made your code a bit more Pythonic (but without altering its flow/algorithm):
def swap(ary, idx1, idx2):
ary[idx1], ary[idx2] = [ary[i] for i in (idx2, idx1)]
def permutations(ordered, movements):
size = len(ordered)
for i in range(1, len(ordered)):
for j in range(movements[i]):
swap(ordered, i-j, i-j-1)
return ordered
numberofcases = input()
for i in range(numberofcases):
sizeofcase = input()
movements = [int(s) for s in raw_input().split()]
ordered = [str(i) for i in range(1, sizeofcase+1)]
ordered = permutations(ordered, movements)
output = " ".join(ordered)
print output
I see it runs correctly in the sample case given at the SPOJ URL you indicate. What is your failing case?