I am trying to store the values obtained from excel sheet cells to a list. The code provided basically collects data from different continuous rows and columns and creates a string of those values. I could work upt o storing the string value but I don't really know how to store the strings in a list, Can anyone help me with this?
for i in range(NR):
print("This TC checks the output for")
for j in range(NC):
inputVariable = str(ws[get_column_letter(ColumnStart+j) + str(rowStart-1)].value)
c = str((ws.cell(row = (rowStart + i),column = (ColumnStart +j)).value))
if (ws.cell(row = (rowStart + i),column = (ColumnStart+j)).value) == (ws.cell(row = (MaxValRow),column = (ColumnStart+j)).value):
b = '(maximum)'
elif (ws.cell(row = (rowStart + i),column = (ColumnStart+j)).value) == (ws.cell(row = (MinValRow),column = (ColumnStart+j)).value):
b = '(minimum)'
else:
b ='(intermediate)'
Commentstr = str(j+1) + '. The value of input ' + inputVariable + ' =' + " " + c + b
# need to create a list here to store the commentstr for each iteration
NR = no. of rows, NC = no. of columns
my_list=[]
for i in range(NR):
x=0
print("This TC checks the output for")
for j in range(NC):
inputVariable = str(ws[get_column_letter(ColumnStart+j) + str(rowStart-1)].value)
c = str((ws.cell(row = (rowStart + i),column = (ColumnStart +j)).value))
if (ws.cell(row = (rowStart + i),column = (ColumnStart+j)).value) == (ws.cell(row = (MaxValRow),column = (ColumnStart+j)).value):
b = '(maximum)'
elif (ws.cell(row = (rowStart + i),column = (ColumnStart+j)).value) == (ws.cell(row = (MinValRow),column = (ColumnStart+j)).value):
b = '(minimum)'
else:
b ='(intermediate)'
Commentstr = str(j+1) + '. The value of input ' + inputVariable + ' =' + " " + c + b
my_list[x]=Commentstr
x+=1
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)
Below is a part of my python script, which reads data in daily automation in Linux system & print it in mail body & sends. my input file changes daily and it works perfectly if input file contains all strings (or) numarical values.
If the input file has empty string/value in any of rows, it throws IndexError and stops printing the data.
f = open('INPUTfile')
lines = f.readlines()
count=len(lines)
f.close()
body1="""
"""
z=0
while (z<count):
test = lines[z]
hello = test.split(',')
a = hello[0:1]
a1 = a[0]
b = hello[1:2]
b1 = b[0]
c = hello[2:3]
c1 = c[0]
d = hello[3:4]
d1 = d[0]
e = hello[4:5]
e1 = e[0]
f = hello[5:6]
f1 = f[0]
g = hello[6:7]
g1 = g[0]
h = hello[7:8]
h1 = h[0]
i = hello[8:9]
i1 = i[0]
j = hello[9:10]
j1 = j[0]
k = hello[10:11]
k1 = k[0]
l = hello[11:12]
l1 = l[0]
m = hello[12:13]
m1 = m[0]
d1 = float(d[0])
g1 = float(g[0])
j1 = float(j[0])
m1 = float(m[0])
if all([d1 < 99.00, j1 < 99.00]):
body1 = body1 + '<tr><td style="font-family:Calibri;"><b>' + a1 + '</b></td><td style="font-family:Calibri;">' + b1 + '</td></td><td style="font-family:Calibri;">' + c1 + '</td></td><td style="font-family:Calibri;color:red">' + str(round(d1,2)) + '</td></td><td style="font-family:Calibri;">' + e1 + '</td><td style="font-family:Calibri;">' + f1 + '</td></td><td style="font-family:Calibri;color:red">' + str(round(g1,2)) + '</td><td style="font-family:Calibri;">' + h1 + '</td><td style="font-family:Calibri;">' + i1 + '</td><td style="font-family:Calibri;">' + str(round(j1,2)) + '</td><td style="font-family:Calibri;">' + k1 + '</td><td style="font-family:Calibri;">' + l1 + '</td><td style="font-family:Calibri;">' + str(round(m1,2)) + '</td></tr>'
z=z+1
My inputfile:
APPU1,2004423,2004417,99.9997,2847,2847,100,7600,7599,99.9846,1248,1248,99.9999
APPU2,,,
APPU3,2004333,2004329,99.9998,2848,2848,100,7593,7592,99.9842,1248,1247,99.9999
APPU4,2004020,2004016,99.9998,2849,2847,100,7596,7595,99.9853,1248,1247,99.9999
please suggest solution to print the data even if the rows in INPUT file contains null values.
I don't understand use of while loop here.
Anyway what you need is an if statement at the starting of while loop.
while (z<count):
test = lines[z]
hello = test.split(',')
if len(hello) < 14: # or whatever number of items required.
z+=1
continue
#rest of your code goes here
If I were you, I would write the code like this.
with open('INPUTfile') as f:
for i, line in enumerate(f):
hello = line.split(',')
#rest of the code.
You can use try except block in python.
try:
<your logic here> or the code
except IndexError:
pass # If IndexError is encountered, pass the control to the loop and continue from the next line
Use this code snippet and check if that solves the problem
for line in lines:
try:
test = line
hello = test.split(',')
a = hello[0:1]
a1 = a[0]
b = hello[1:2]
b1 = b[0]
c = hello[2:3]
c1 = c[0]
d = hello[3:4]
d1 = d[0]
e = hello[4:5]
e1 = e[0]
f = hello[5:6]
f1 = f[0]
g = hello[6:7]
g1 = g[0]
h = hello[7:8]
h1 = h[0]
i = hello[8:9]
i1 = i[0]
j = hello[9:10]
j1 = j[0]
k = hello[10:11]
k1 = k[0]
l = hello[11:12]
l1 = l[0]
m = hello[12:13]
m1 = m[0]
d1 = float(d[0])
g1 = float(g[0])
j1 = float(j[0])
m1 = float(m[0])
except IndexError:
pass
How would I be able to improve the speed of this monty hall program, interestingly, the same code written using BBC BASIC for Windows completes the task in half the time of the Python code.
Python Code:
import random
t = 10000001
j = 0
k = 0
for a in range(1, t):
p = int(random.random() * 3) + 1
g = int(random.random() * 3) + 1
if p == g:
r = int(random.random() * 2) + 1
if p == 1:
r += 1
if p == 2 and r == 2:
r = 3
else:
r = p ^ g
s = g
f = g ^ r
if s == p:
j = j + 1
if f == p:
k = k + 1
print(f"After a total of {t - 1} trials,")
print(f"The 'sticker' won {j} times ({int(j/t*100)}%)")
print(f"The 'swapper' won {k} times ({int(k/t*100)}%)")
BBC BASIC for Windows code
T% = 10000000
for A% = 1 to T%
P% = rnd(3)
G% = rnd(3)
if P% = G% then
R% = rnd(2)
if P% = 1 then R% += 1
if P% = 2 and R% = 2 then R% = 3
else
R% = P% eor G%
endif
S% = G%
F% = G% eor R%
if S% = P% then J% = J% + 1
if F% = P% then K% = K% + 1
next
print "After a total of ";T%;" trials,"
print "The 'sticker' won ";J%;" times (";int(J%/T%*100);"%)"
print "The 'swapper' won ";K%;" times (";int(K%/T%*100);"%)"
First thing is changing your import from:
import random
to
from random import random
then using:
p = int(random() * 3) + 1
g = int(random() * 3) + 1
Second thing you can do is change your:
if s == p:
j = j + 1
if f == p:
k = k + 1
Into:
if s == p:
j = j + 1
elif f == p:
k = k + 1
I wrote this script below which converts number to it's spelling.
no = raw_input("Enter a number: ")
strcheck = str(no)
try:
val = int(no)
except ValueError:
print("sayi degil")
raise SystemExit
lencheck = str(no)
if len(lencheck) > 6:
print("Bu sayi cok buyuk !")
raise SystemExit
n = int(no)
print(n)
def int2word(n):
n3 = []
r1 = ""
ns = str(n)
for k in range(3, 33, 3):
r = ns[-k:]
q = len(ns) - k
if q < -2:
break
else:
if q >= 0:
n3.append(int(r[:3]))
elif q >= -1:
n3.append(int(r[:2]))
elif q >= -2:
n3.append(int(r[:1]))
r1 = r
#print(n3)
nw = ""
for i, x in enumerate(n3):
b1 = x % 10
b2 = (x % 100)//10
b3 = (x % 1000)//100
if x == 0:
continue
else:
t = binler[i]
if b2 == 0:
nw = birler[b1] + t + nw
elif b2 == 1:
nw = onlar[1] + birler[b1] + t + nw
elif b2 > 1:
nw = onlar[b2] + birler[b1] + t + nw
if b3 > 0:
nw = birler[b3] + "yuz " + nw
return nw
birler = ["", " ","iki ","uc ","dort ", "bes ", "alti ","yedi ","sekiz ","dokuz "]
onlar = ["", "on ", "yirmi ", "otuz ", "kirk ", "elli ", "altmis ", "yetmis ", "seksen ", "doksan "]
binler = ["", "bin"]
print int2word(n)
This scripts works pretty well on Python2.7.
But when I try to run it with python3.3
It gives me error below:
File "numtospell.py", line 58
if x == 0:
^
TabError: inconsistent use of tabs and spaces in indentation
I've googled it for hours but cannot find a suitable solution. What do I do to fix this?
Thanks for any help.
You are mixing tabs and spaces.
Python 3 explicitly disallows this. Use spaces only for indentation.
Quoting from the Python Style Guide (PEP 8):
Spaces are the preferred indentation method.
Tabs should be used solely to remain consistent with code that is already indented with tabs.
Python 3 disallows mixing the use of tabs and spaces for indentation.
Emphasis mine.
Almost all editors can be configured to replace tabs with spaces when typing, as well as do a search and replace operation that replaces existing tabs with spaces.