I want to create a multiplication table in the following format:
| 1 2 ... 9
---------...----
1 | 1 2 ... 9
2 | 2 4 ... 18
...
9 | 9 18 ... 81
Properly align numbers to the right
vertical line after first column and horizontal line after first row.
(the ... are just here for brevity)
So far I figured out the alignment:
for row in range(1,10):
s = ''
for col in range(1,10):
s += '{:3} '.format(row * col)
print(s, sep="\t")
But how do I add the lines, i.e. they shouldn't be iterated in the loop.
Are you looking for something like this:
for row in range(1,10):
s = str(row) + ' |'
if(row == 1):
for i in range(1, 2):
x = ' ' + ' |'
for j in range(1, 10):
x += '{:3} '.format(i * j)
print(x, sep="\t")
print('----' * 10)
for col in range(1,10):
s += '{:3} '.format(row * col)
print(s, sep="\t")
Output:
| 1 2 3 4 5 6 7 8 9
----------------------------------------
1 | 1 2 3 4 5 6 7 8 9
2 | 2 4 6 8 10 12 14 16 18
3 | 3 6 9 12 15 18 21 24 27
4 | 4 8 12 16 20 24 28 32 36
5 | 5 10 15 20 25 30 35 40 45
6 | 6 12 18 24 30 36 42 48 54
7 | 7 14 21 28 35 42 49 56 63
8 | 8 16 24 32 40 48 56 64 72
9 | 9 18 27 36 45 54 63 72 81
Related
I have dataframe i want to move column name to left from specific column. original dataframe have many columns can not do this by rename columns
df=pd.DataFrame({'A':[1,3,4,7,8,11,1,15,20,15,16,87],
'H':[1,3,4,7,8,11,1,15,78,15,16,87],
'N':[1,3,4,98,8,11,1,15,20,15,16,87],
'p':[1,3,4,9,8,11,1,15,20,15,16,87],
'B':[1,3,4,6,8,11,1,19,20,15,16,87],
'y':[0,0,0,0,1,1,1,0,0,0,0,0]})
print((df))
A H N p B y
0 1 1 1 1 1 0
1 3 3 3 3 3 0
2 4 4 4 4 4 0
3 7 7 98 9 6 0
4 8 8 8 8 8 1
5 11 11 11 11 11 1
6 1 1 1 1 1 1
7 15 15 15 15 19 0
8 20 78 20 20 20 0
9 15 15 15 15 15 0
10 16 16 16 16 16 0
11 87 87 87 87 87 0
Here i want to remove label N first dataframe after removing label N
A H p B y
0 1 1 1 1 1 0
1 3 3 3 3 3 0
2 4 4 4 4 4 0
3 7 7 98 9 6 0
4 8 8 8 8 8 1
5 11 11 11 11 11 1
6 1 1 1 1 1 1
7 15 15 15 15 19 0
8 20 78 20 20 20 0
9 15 15 15 15 15 0
10 16 16 16 16 16 0
11 87 87 87 87 87 0
Rrquired output:
A H P B y
0 1 1 1 1 1 0
1 3 3 3 3 3 0
2 4 4 4 4 4 0
3 7 7 98 9 6 0
4 8 8 8 8 8 1
5 11 11 11 11 11 1
6 1 1 1 1 1 1
7 15 15 15 15 19 0
8 20 78 20 20 20 0
9 15 15 15 15 15 0
10 16 16 16 16 16 0
11 87 87 87 87 87 0
Here last column can be ignore
Note: in original dataframe have many columns , can not rename columns , so need some auto method to shift column names lef
You can do
df.columns=sorted(df.columns.str.replace('N',''),key=lambda x : x=='')
df
A H p B y
0 1 1 1 1 1 0
1 3 3 3 3 3 0
2 4 4 4 4 4 0
3 7 7 98 9 6 0
4 8 8 8 8 8 1
5 11 11 11 11 11 1
6 1 1 1 1 1 1
7 15 15 15 15 19 0
8 20 78 20 20 20 0
9 15 15 15 15 15 0
10 16 16 16 16 16 0
11 87 87 87 87 87 0
Replace the columns with your own custom list.
>>> cols = list(df.columns)
>>> cols.remove('N')
>>> df.columns = cols + ['']
Output
>>> df
A H p B y
0 1 1 1 1 1 0
1 3 3 3 3 3 0
2 4 4 4 4 4 0
3 7 7 98 9 6 0
4 8 8 8 8 8 1
5 11 11 11 11 11 1
6 1 1 1 1 1 1
7 15 15 15 15 19 0
8 20 78 20 20 20 0
9 15 15 15 15 15 0
10 16 16 16 16 16 0
11 87 87 87 87 87 0
Trying to let the user input a number, and print a table according to the square of its size. Here's an example.
Size--> 3
0 1 2
3 4 5
6 7 8
Size--> 4
0 1 2 3
4 5 6 7
8 9 10 11
12 13 14 15
Size--> 6
0 1 2 3 4 5
6 7 8 9 10 11
12 13 14 15 16 17
18 19 20 21 22 23
24 25 26 27 28 29
30 31 32 33 34 35
Size--> 9
0 1 2 3 4 5 6 7 8
9 10 11 12 13 14 15 16 17
18 19 20 21 22 23 24 25 26
27 28 29 30 31 32 33 34 35
36 37 38 39 40 41 42 43 44
45 46 47 48 49 50 51 52 53
54 55 56 57 58 59 60 61 62
63 64 65 66 67 68 69 70 71
72 73 74 75 76 77 78 79 80
Here's is the code that i have tried.
length=int(input('Size--> '))
size=length*length
biglist=[]
for i in range(size):
biglist.append(i)
biglist = [str(i) for i in biglist]
for i in range(0, len(biglist), length):
print(' '.join(biglist[i: i+length]))
but instead here's what i got
Size--> 3
0 1 2
3 4 5
6 7 8
Size--> 4
0 1 2 3
4 5 6 7
8 9 10 11
12 13 14 15
Size--> 6
0 1 2 3 4 5
6 7 8 9 10 11
12 13 14 15 16 17
18 19 20 21 22 23
24 25 26 27 28 29
30 31 32 33 34 35
As you can see the rows are not aligned properly like the example.
What's the simplest way of presenting it in a proper alignment? Thx :)
Using .format on string with right aligning.
And strlen is the number of characters required for each number.
length = int(input('Size--> '))
size = length*length
biglist = []
for i in range(size):
biglist.append(i)
biglist = [str(i) for i in biglist]
strlen = len(str(length**2-1))+1
for i in range(0, len(biglist), length):
# print(' '.join(biglist[i: i+length]))
for x in biglist[i: i+length]:
print(f"{x:>{strlen}}", end='')
print()
I've a list of number from 1 to 53. I am trying to calculate 1) the quarter of a week and 2) the number of that week within that quarter using numeric week numbers. (if 53, needs to be qtr 4 wk 14, if 27 needs to be 3rd quarter wk 1). Got this working in excel, but not in python? Any thoughts?
tried the following, but at each try I've an issue with the wk's like 13 or 27 depending on the method I'm using.
13 -> should be qtr 1 , 27 -> should be 3 qtr.
df['qtr1'] = df['wk']//13
df['qtr2']=(np.maximum((df['wk']-1),1)/13)+1
df['qtr3']=((df1['wk']-1)//13)
df['qtr4'] = df['qtr2'].astype(int)
Results are awkward
wk qtr qtr2 qtr3 qtr4
1.0 0 1.076923 -1.0 1
13.0 1(wrong) 1.923077 0.0 1
14.0 1 2.000000 1.0 2
27.0 2 3.000000 1.0 2 (wrong)
28.0 2 3.076923 2.0 3
You can convert your weeks to integers, by using astype:
df['wk'] = df['wk'].astype(int)
You should subtract it with one first, like:
df['qtr'] = ((df['wk']-1) // 13) + 1
df['weekinqtr'] = (df['wk']-1) % 13 + 1
since 13//13 will be 1, not zero. This gives us:
>>> df
wk qtr weekinqtr
0 1 1 1
1 13 1 13
2 14 2 1
3 26 2 13
4 27 3 1
5 28 3 2
If you want extra columns per quarter, you can use get_dummies(..) [pandas-doc] to obtain a one-hot encoding per quarter:
>>> df.join(pd.get_dummies(df['qtr'], prefix='qtr'))
wk qtr weekinqtr qtr_1 qtr_2 qtr_3
0 1 1 1 1 0 0
1 13 1 13 1 0 0
2 14 2 1 0 1 0
3 26 2 13 0 1 0
4 27 3 1 0 0 1
5 28 3 2 0 0 1
Using div // and modulo % work for what you want I think
In [254]: df = pd.DataFrame({'week':range(52)})
In [255]: df['qtr'] = (df['week'] // 13) + 1
In [256]: df['qtr_week'] = df['week'] % 13
In [257]: df.loc[(df['qtr_week'] ==0),'qtr_week']=13
In [258]: df
Out[258]:
week qtr qtr_week
0 1 1 1
1 2 1 2
2 3 1 3
3 4 1 4
4 5 1 5
5 6 1 6
6 7 1 7
7 8 1 8
8 9 1 9
9 10 1 10
10 11 1 11
11 12 1 12
12 13 2 13
13 14 2 1
14 15 2 2
15 16 2 3
16 17 2 4
17 18 2 5
18 19 2 6
19 20 2 7
20 21 2 8
21 22 2 9
22 23 2 10
23 24 2 11
24 25 2 12
25 26 3 13
26 27 3 1
27 28 3 2
28 29 3 3
29 30 3 4
30 31 3 5
31 32 3 6
32 33 3 7
33 34 3 8
34 35 3 9
35 36 3 10
36 37 3 11
37 38 3 12
38 39 4 13
39 40 4 1
40 41 4 2
41 42 4 3
42 43 4 4
43 44 4 5
44 45 4 6
45 46 4 7
46 47 4 8
47 48 4 9
48 49 4 10
49 50 4 11
50 51 4 12
I have an extension to this question. I have lists of lists in my columns and I need to expand the rows one step further. If I just repeat the steps it splits my strings into letters. Could you suggest a smart way around? Thanks!
d1 = pd.DataFrame({'column1': [['ana','bob',[1,2,3]],['dona','elf',[4,5,6]],['gear','hope',[7,8,9]]],
'column2':[10,20,30],
'column3':[44,55,66]})
d2 = pd.DataFrame.from_records(d1.column1.tolist()).stack().reset_index(level=1, drop=True).rename('column1')
d1_d2 = d1.drop('column1', axis=1).join(d2).reset_index(drop=True)[['column1','column2', 'column3']]
d1_d2
It seems you need flatten nested lists:
from collections import Iterable
def flatten(coll):
for i in coll:
if isinstance(i, Iterable) and not isinstance(i, str):
for subc in flatten(i):
yield subc
else:
yield i
d1['column1'] = d1['column1'].apply(lambda x: list(flatten(x)))
print (d1)
column1 column2 column3
0 [ana, bob, 1, 2, 3] 10 44
1 [dona, elf, 4, 5, 6] 20 55
2 [gear, hope, 7, 8, 9] 30 66
And then use your solution:
d2 = (pd.DataFrame(d1.column1.tolist())
.stack()
.reset_index(level=1, drop=True)
.rename('column1'))
d1_d2 = (d1.drop('column1', axis=1)
.join(d2)
.reset_index(drop=True)[['column1','column2', 'column3']])
print (d1_d2)
column1 column2 column3
0 ana 10 44
1 bob 10 44
2 1 10 44
3 2 10 44
4 3 10 44
5 dona 20 55
6 elf 20 55
7 4 20 55
8 5 20 55
9 6 20 55
10 gear 30 66
11 hope 30 66
12 7 30 66
13 8 30 66
14 9 30 66
Assuming the expected result is same as jezrael.
pandas >= 0.25.0
d1 = d1.explode('column1').explode('column1').reset_index(drop=True)
d1:
column1 column2 column3
0 ana 10 44
1 bob 10 44
2 1 10 44
3 2 10 44
4 3 10 44
5 dona 20 55
6 elf 20 55
7 4 20 55
8 5 20 55
9 6 20 55
10 gear 30 66
11 hope 30 66
12 7 30 66
13 8 30 66
14 9 30 66
I have a list of 1 column and 50 rows.
I want to divide it into 5 segments. And each segment has to become a column of a dataframe. I do not want the NAN to appear (figure2). How can I solve that?
Like this:
df = pd.DataFrame(result_list)
AWA=df[:10]
REM=df[10:20]
S1=df[20:30]
S2=df[30:40]
SWS=df[40:50]
result = pd.concat([AWA, REM, S1, S2, SWS], axis=1)
result
Figure2
You can use numpy's reshape function:
result_list = [i for i in range(50)]
pd.DataFrame(np.reshape(result_list, (10, 5), order='F'))
Out:
0 1 2 3 4
0 0 10 20 30 40
1 1 11 21 31 41
2 2 12 22 32 42
3 3 13 23 33 43
4 4 14 24 34 44
5 5 15 25 35 45
6 6 16 26 36 46
7 7 17 27 37 47
8 8 18 28 38 48
9 9 19 29 39 49