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Please I need a code to develop multiplication table and currency converter in puthon
multiplication table and currency converter
29 Réponses
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import pprint
n = 12
m = list(list(range(1*i, (n+1)*i, i)) for i in range(1, n+1))
pprint.pprint(m)
[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
[2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24],
[3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36],
[4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48],
[5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60],
[6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72],
[7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, 84],
[8, 16, 24, 32, 40, 48, 56, 64, 72, 80, 88, 96],
[9, 18, 27, 36, 45, 54, 63, 72, 81, 90, 99, 108],
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120],
[11, 22, 33, 44, 55, 66, 77, 88, 99, 110, 121, 132],
[12, 24, 36, 48, 60, 72, 84, 96, 108, 120, 132, 144]]
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max_width = len(str(m[-1][-1])) + 1
for i in m:
i = [str (j).rjust(max_width) for j in i]
print (".join(i))
1 2 3 4 5 6 7 8 9 10 11 12
2 4 6 8 10 12 14 16 18 20 22 24
3 6 9 12 15 18 21 24 27 30 33 36
4 8 12 16 20 24 28 32 36 40 44 48
5 10 15 20 25 30 35 40 45 50 55 60
6 12 18 24 30 36 42 48 54 60 66 72
7 14 21 28 35 42 49 56 63 70 77 84
8 16 24 32 40 48 56 64 72 80 88 96
9 18 27 36 45 54 63 72 81 90 99 108
10 20 30 40 50 60 70 80 90 100 110 120
11 22 33 44 55 66 77 88 99 110 121 132
12 24 36 48 60 72 84 96 108 120 132 144
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I see, I just want you to be my mentor. show me steps and advice on what to do to develop my self
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wow! I get it would have love to pay for your service which am doubtful of because you are a pro and am still in school
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Russia! that's nice hope you are enjoying the world cup. anyway I really appreciate you, thanks a million
0
Specify the language in which you want this table to be written
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Thanks sir. am just learning python. so I will love you to help me in python language
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Now that we have the list of integers that is in the form that we want, we have to convert them to strings that are correctly justified with a width from one greater than the largest integer in the list of lists (the last integer) using the default argument '' for fillchar.
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and demonstrate the elasticity of the interval with a different size, for example. n = 9
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n=9
m = list(list(range(1*i,(n+1)*i, i)) for i in range(1,n+1))
for i in m:
i = [str(j).rjust(len(str(m[-1][-1]))+1) for j in i]
print(''.join(i))
1 2 3 4 5 6 7 8 9
2 4 6 8 10 12 14 16 18
3 6 9 12 15 18 21 24 27
4 8 12 16 20 24 28 32 36
5 10 15 20 25 30 35 40 45
6 12 18 24 30 36 42 48 54
7 14 21 28 35 42 49 56 63
8 16 24 32 40 48 56 64 72
9 18 27 36 45 54 63 72 81
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Thanks Paswer. I really appreciate
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Also procedure for converting from one currency to another using python
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Well, I don't need to be rushed.
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Thanks. I don't mean to rush you. I will appreciate you spare time sir
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I con see you are really do at this
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You can use the vectorized str methods to replace unwanted characters and then apply the type to the int:
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In [81]:
df[df.columns[1:]] = df[df.columns[1:]].apply(lambda x: x.str.replace('#x27;,'')).apply(lambda x: x.str.replace(',','')).astype(np.int64)
df
Out[81]:
state 1st 2nd 3rd
index
0 California 11593820 109264246 8496273
1 New York 10861680 45336041 6317300
2 Florida 7942848 69369589 4697244
3 Texas 7536817 61830712 5736941
dtype теперь подтверждено изменение:
In [82]:
df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 4 entries, 0 to 3
Data columns (total 4 columns):
state 4 non-null object
1st 4 non-null int64
2nd 4 non-null int64
3rd 4 non-null int64
dtypes: int64(3), object(1)
memory usage: 160.0+ bytes
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dtype change now confirmed:
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In [82]:
df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 4 entries, 0 to 3
Data columns (total 4 columns):
state 4 non-null object
1st 4 non-null int64
2nd 4 non-null int64
3rd 4 non-null int64
dtypes: int64(3), object(1)
memory usage: 160.0+ bytes
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Other way: