When I write the following code I get garbage for an output. It is just a simple program to find prime numbers. It works when the first for loops range only goes up to 1000 but once the range becomes large the program fail's to output meaningful data
output = open("output.dat", 'w')
for i in range(2, 10000):
prime = 1
for j in range(2, i-1):
if i%j == 0:
prime = 0
j = i-1
if prime == 1:
output.write(str(i) + " " )
output.close()
print "writing finished"
This is a known Notepad bug. Check out
http://blogs.msdn.com/oldnewthing/archive/2007/04/17/2158334.aspx
The classic way to trigger this bug is to put "Bush hid the facts" in a file, save it, reopen it, and scream about conspiracy theories, but I guess "2 3 5 7 11 13 17" works too, except that you don't get to scream about conspiracy theories.
You're setting a single variable named prime ten thousand times to 1, then 9998 times possibly setting it to 0, and finally (if it's not been set to 0) outputting one incomplete line (no line-end). I suspect that's not what you want to do! Maybe something like...:
output = open("output.dat", 'w')
for i in range(2, 10000):
prime = 1
for j in range(2, i-1):
if i%j == 0:
prime = 0
break
if prime == 1:
output.write(str(i) + " " )
output.close()
print "writing finished"
Note the very different indentation from what you had posted. I also used break to break out of an inner loop, which I think was what you meant where you wrote j = i - 1 (which would in fact have absolutely no effect since j would just be set to its next natural value in the very next leg of that inner loop, which would still run to the end).
With fixed indentation (which I'll have to assume is a bad paste job, otherwise I don't think it would run) your code outputs fine for me :
2 3 5 7 11 13 17 19 23 29 31 37 41 43 47 53 59 61 67 71 73 79 83 89 97 101 103 107 109 113 127 131 137 139 149 151 157 163 167 173 179 181 191 193 197 199 211 223 227 229 233 239 241 251 257 263 269 271 277 281 283 293 307 311 313 317 331 337 347 349 353 359 367 373 379 383 389 397 401 409 419 421 431 433 439 443 449 457 461 463 467 479 487 491 499 503 509 521 523 541 547 557 563 569 571 577 587 593 599 601 607 613 617 619 631 641 643 647 653 659 661 673 677 683 691 701 709 719 727 733 739 743 751 757 761 769 773 787 797 809 811 821 823 827 829 839 853 857 859 863 877 881 883 887 907 911 919 929 937 941 947 953 967 971 977 983 991 997 1009 1013 1019 1021 1031 1033 1039 1049 1051 1061 1063 1069 1087 1091 1093 1097 1103 1109 1117 1123 1129 1151 1153 1163 1171 1181 1187 1193 1201 1213 1217 1223 1229 1231 1237 1249 1259 1277 1279 1283 1289 1291 1297 1301 1303 1307 1319 1321 1327 1361 1367 1373 1381 1399 1409 1423 1427 1429 1433 1439 1447 1451 1453 1459 1471 1481 1483 1487 1489 1493 1499 1511 1523 1531 1543 1549 1553 1559 1567 1571 1579 1583 1597 1601 1607 1609 1613 1619 1621 1627 1637 1657 1663 1667 1669 1693 1697 1699 1709 1721 1723 1733 1741 1747 1753 1759 1777 1783 1787 1789 1801 1811 1823 1831 1847 1861 1867 1871 1873 1877 1879 1889 1901 1907 1913 1931 1933 1949 1951 1973 1979 1987 1993 1997 1999 2003 2011 2017 2027 2029 2039 2053 2063 2069 2081 2083 2087 2089 2099 2111 2113 2129 2131 2137 2141 2143 2153 2161 2179 2203 2207 2213 2221 2237 2239 2243 2251 2267 2269 2273 2281 2287 2293 2297 2309 2311 2333 2339 2341 2347 2351 2357 2371 2377 2381 2383 2389 2393 2399 2411 2417 2423 2437 2441 2447 2459 2467 2473 2477 2503 2521 2531 2539 2543 2549 2551 2557 2579 2591 2593 2609 2617 2621 2633 2647 2657 2659 2663 2671 2677 2683 2687 2689 2693 2699 2707 2711 2713 2719 2729 2731 2741 2749 2753 2767 2777 2789 2791 2797 2801 2803 2819 2833 2837 2843 2851 2857 2861 2879 2887 2897 2903 2909 2917 2927 2939 2953 2957 2963 2969 2971 2999 3001 3011 3019 3023 3037 3041 3049 3061 3067 3079 3083 3089 3109 3119 3121 3137 3163 3167 3169 3181 3187 3191 3203 3209 3217 3221 3229 3251 3253 3257 3259 3271 3299 3301 3307 3313 3319 3323 3329 3331 3343 3347 3359 3361 3371 3373 3389 3391 3407 3413 3433 3449 3457 3461 3463 3467 3469 3491 3499 3511 3517 3527 3529 3533 3539 3541 3547 3557 3559 3571 3581 3583 3593 3607 3613 3617 3623 3631 3637 3643 3659 3671 3673 3677 3691 3697 3701 3709 3719 3727 3733 3739 3761 3767 3769 3779 3793 3797 3803 3821 3823 3833 3847 3851 3853 3863 3877 3881 3889 3907 3911 3917 3919 3923 3929 3931 3943 3947 3967 3989 4001 4003 4007 4013 4019 4021 4027 4049 4051 4057 4073 4079 4091 4093 4099 4111 4127 4129 4133 4139 4153 4157 4159 4177 4201 4211 4217 4219 4229 4231 4241 4243 4253 4259 4261 4271 4273 4283 4289 4297 4327 4337 4339 4349 4357 4363 4373 4391 4397 4409 4421 4423 4441 4447 4451 4457 4463 4481 4483 4493 4507 4513 4517 4519 4523 4547 4549 4561 4567 4583 4591 4597 4603 4621 4637 4639 4643 4649 4651 4657 4663 4673 4679 4691 4703 4721 4723 4729 4733 4751 4759 4783 4787 4789 4793 4799 4801 4813 4817 4831 4861 4871 4877 4889 4903 4909 4919 4931 4933 4937 4943 4951 4957 4967 4969 4973 4987 4993 4999 5003 5009 5011 5021 5023 5039 5051 5059 5077 5081 5087 5099 5101 5107 5113 5119 5147 5153 5167 5171 5179 5189 5197 5209 5227 5231 5233 5237 5261 5273 5279 5281 5297 5303 5309 5323 5333 5347 5351 5381 5387 5393 5399 5407 5413 5417 5419 5431 5437 5441 5443 5449 5471 5477 5479 5483 5501 5503 5507 5519 5521 5527 5531 5557 5563 5569 5573 5581 5591 5623 5639 5641 5647 5651 5653 5657 5659 5669 5683 5689 5693 5701 5711 5717 5737 5741 5743 5749 5779 5783 5791 5801 5807 5813 5821 5827 5839 5843 5849 5851 5857 5861 5867 5869 5879 5881 5897 5903 5923 5927 5939 5953 5981 5987 6007 6011 6029 6037 6043 6047 6053 6067 6073 6079 6089 6091 6101 6113 6121 6131 6133 6143 6151 6163 6173 6197 6199 6203 6211 6217 6221 6229 6247 6257 6263 6269 6271 6277 6287 6299 6301 6311 6317 6323 6329 6337 6343 6353 6359 6361 6367 6373 6379 6389 6397 6421 6427 6449 6451 6469 6473 6481 6491 6521 6529 6547 6551 6553 6563 6569 6571 6577 6581 6599 6607 6619 6637 6653 6659 6661 6673 6679 6689 6691 6701 6703 6709 6719 6733 6737 6761 6763 6779 6781 6791 6793 6803 6823 6827 6829 6833 6841 6857 6863 6869 6871 6883 6899 6907 6911 6917 6947 6949 6959 6961 6967 6971 6977 6983 6991 6997 7001 7013 7019 7027 7039 7043 7057 7069 7079 7103 7109 7121 7127 7129 7151 7159 7177 7187 7193 7207 7211 7213 7219 7229 7237 7243 7247 7253 7283 7297 7307 7309 7321 7331 7333 7349 7351 7369 7393 7411 7417 7433 7451 7457 7459 7477 7481 7487 7489 7499 7507 7517 7523 7529 7537 7541 7547 7549 7559 7561 7573 7577 7583 7589 7591 7603 7607 7621 7639 7643 7649 7669 7673 7681 7687 7691 7699 7703 7717 7723 7727 7741 7753 7757 7759 7789 7793 7817 7823 7829 7841 7853 7867 7873 7877 7879 7883 7901 7907 7919 7927 7933 7937 7949 7951 7963 7993 8009 8011 8017 8039 8053 8059 8069 8081 8087 8089 8093 8101 8111 8117 8123 8147 8161 8167 8171 8179 8191 8209 8219 8221 8231 8233 8237 8243 8263 8269 8273 8287 8291 8293 8297 8311 8317 8329 8353 8363 8369 8377 8387 8389 8419 8423 8429 8431 8443 8447 8461 8467 8501 8513 8521 8527 8537 8539 8543 8563 8573 8581 8597 8599 8609 8623 8627 8629 8641 8647 8663 8669 8677 8681 8689 8693 8699 8707 8713 8719 8731 8737 8741 8747 8753 8761 8779 8783 8803 8807 8819 8821 8831 8837 8839 8849 8861 8863 8867 8887 8893 8923 8929 8933 8941 8951 8963 8969 8971 8999 9001 9007 9011 9013 9029 9041 9043 9049 9059 9067 9091 9103 9109 9127 9133 9137 9151 9157 9161 9173 9181 9187 9199 9203 9209 9221 9227 9239 9241 9257 9277 9281 9283 9293 9311 9319 9323 9337 9341 9343 9349 9371 9377 9391 9397 9403 9413 9419 9421 9431 9433 9437 9439 9461 9463 9467 9473 9479 9491 9497 9511 9521 9533 9539 9547 9551 9587 9601 9613 9619 9623 9629 9631 9643 9649 9661 9677 9679 9689 9697 9719 9721 9733 9739 9743 9749 9767 9769 9781 9787 9791 9803 9811 9817 9829 9833 9839 9851 9857 9859 9871 9883 9887 9901 9907 9923 9929 9931 9941 9949 9967 9973
EDIT the version of indentation I ran:
output = open("output.dat", 'w')
for i in range(2, 10000):
prime = 1
for j in range(2, i-1):
if i%j == 0:
prime = 0
j = i-1
if prime == 1:
output.write(str(i) + " " )
output.close()
print "writing finished"
Your second for should be nested in the first for.
Also, this looks like a homework question. It is not clear how your output is garbage - does it not compute what you want? Or is the output scrambled? Post a copy of the output so we can see!
Don't you want your loops to be nested?
output = open("output.dat", 'w')
for i in range(2, 10000):
prime = 1
for j in range(2, i-1):
if i%j == 0:
prime = 0
j = i-1
if prime == 1:
output.write(str(i) + " " )
output.close()
print "writing finished"
so, you set prime to 1, 9998 times
then you use the final value of i (10000?, 10001?) as an end value
....
to summarize, you have serious indention problems....
Related
I have similar data as below in my pandas dataframe.
Date
A
B
C
D
01-01-2022
10000
1700
1457
327
02-01-2022
17000
3000
1245
526
03-01-2022
16000
2624
1478
632
04-01-2022
10138
1745
1325
800
05-01-2022
4761
1789
1475
952
06-01-2022
5000
1874
1423
1105
07-01-2022
3000
1965
1421
895
08-01-2022
4000
1847
1420
1410
09-01-2022
3001
1654
1418
564
10-01-2022
3002
1754
1417
1715
11-01-2022
3003
1598
1415
564
12-01-2022
3004
1515
1414
2020
13-01-2022
3005
1433
1412
564
14-01-2022
3006
1350
1411
2325
15-01-2022
3007
1268
1409
456
Table
How can I get separate plots side by side as date vs A, Date vs B, Date Vs C and so on, using python?
I am still learning, new to python and data visualization.
Try this, using pandas plot with subplots equal to True, and layout with (row, column) tuple:
df['Date'] = pd.to_datetime(df['Date'], format='%d-%m-%Y')
df.set_index('Date').plot(subplots=True, layout=(1,4), figsize=(15,7))
Output:
I have daily timeseries data from 9am to 3pm but, when I am going plot these data in matplotlib, it is taking 24 hours as a day, but I want it take 9AM TO 3PM as a day . How do I get continuous daily graph for only 9 AM TO 3 PM?
This is what I got from my code.
Here is my sample data. I would like to have time-date v/s close plot without any data gap. Please help me.
Pardon me for any mistake here!
close lot1 lot2 time-date
0 800.0 25 50 2020-09-15 11:01:00
1 900.0 25 50 2020-09-15 14:33:00
2 885.85 50 75 2020-09-16 11:45:00
3 791.4 50 125 2020-09-16 12:50:00
4 1082.45 50 75 2020-09-16 14:30:00
5 1060.1 25 125 2020-09-16 14:35:00
6 855.1 50 100 2020-09-17 11:36:00
7 830.0 250 125 2020-09-17 11:39:00
8 815.0 25 125 2020-09-17 11:40:00
9 804.8 25 400 2020-09-17 11:41:00
10 803.0 275 400 2020-09-17 11:44:00
11 791.0 150 650 2020-09-17 11:54:00
12 791.0 100 650 2020-09-17 11:55:00
13 780.65 25 900 2020-09-17 11:59:00
14 784.8 25 925 2020-09-17 12:01:00
15 825.0 25 925 2020-09-17 12:16:00
16 812.3 25 925 2020-09-17 13:25:00
17 816.7 25 950 2020-09-17 14:23:00
18 811.0 25 950 2020-09-17 14:48:00
19 764.5 25 975 2020-09-17 15:11:00
20 808.95 100 1000 2020-09-17 15:20:00
21 805.85 50 1100 2020-09-17 15:24:00
22 798.85 25 1125 2020-09-17 15:27:00
23 812.45 25 1150 2020-09-18 09:17:00
24 814.9 50 1225 2020-09-18 09:18:00
25 840.95 25 1225 2020-09-18 09:19:00
26 839.0 25 1225 2020-09-18 09:20:00
27 827.1 25 1175 2020-09-18 09:23:00
28 812.0 100 1150 2020-09-18 09:28:00
29 770.0 100 1200 2020-09-18 09:32:00
30 784.95 25 1200 2020-09-18 09:33:00
31 790.0 25 1325 2020-09-18 09:35:00
32 788.7 25 1325 2020-09-18 09:37:00
33 789.25 75 1375 2020-09-18 09:38:00
34 810.95 25 1375 2020-09-18 09:42:00
35 827.3 25 1375 2020-09-18 09:43:00
36 821.25 25 1400 2020-09-18 09:45:00
37 809.45 25 1375 2020-09-18 09:57:00
38 820.6 50 1400 2020-09-18 10:01:00
39 835.15 50 1425 2020-09-18 10:04:00
40 832.9 100 1425 2020-09-18 10:05:00
41 839.5 25 1425 2020-09-18 10:07:00
42 831.85 25 1475 2020-09-18 10:09:00
43 808.0 50 1400 2020-09-18 10:14:00
44 795.0 25 1400 2020-09-18 10:17:00
45 780.0 50 1350 2020-09-18 10:26:00
46 802.7 100 1350 2020-09-18 10:28:00
47 792.5 50 1425 2020-09-18 10:29:00
48 790.7 75 1425 2020-09-18 10:30:00
49 793.0 25 1425 2020-09-18 10:34:00
50 789.65 25 1425 2020-09-18 10:35:00
51 796.9 50 1425 2020-09-18 10:37:00
52 791.5 25 1425 2020-09-18 10:38:00
53 797.1 50 1475 2020-09-18 10:39:00
54 760.0 50 1475 2020-09-18 10:41:00
55 780.65 100 1475 2020-09-18 10:42:00
56 782.4 50 1475 2020-09-18 10:43:00
57 780.0 100 1550 2020-09-18 10:45:00
58 788.6 75 1650 2020-09-18 10:50:00
59 794.75 25 1650 2020-09-18 10:53:00
60 792.8 150 1650 2020-09-18 10:54:00
61 806.5 150 1650 2020-09-18 10:55:00
62 801.0 50 1775 2020-09-18 10:57:00
63 789.4 50 1775 2020-09-18 10:58:00
64 804.55 25 1775 2020-09-18 11:00:00
65 792.0 25 1775 2020-09-18 11:03:00
66 793.9 50 1775 2020-09-18 11:05:00
67 785.1 225 1850 2020-09-18 11:06:00
68 782.45 50 1850 2020-09-18 11:07:00
69 778.05 50 1850 2020-09-18 11:08:00
70 766.2 175 2000 2020-09-18 11:12:00
71 772.1 75 2000 2020-09-18 11:13:00
72 758.9 100 2200 2020-09-18 11:14:00
73 771.0 250 2200 2020-09-18 11:15:00
74 764.7 25 2200 2020-09-18 11:16:00
75 777.45 125 2450 2020-09-18 11:19:00
76 778.2 25 2550 2020-09-18 11:22:00
77 777.85 25 2550 2020-09-18 11:23:00
78 783.85 125 2600 2020-09-18 11:24:00
79 776.8 100 2700 2020-09-18 11:26:00
80 776.2 75 2700 2020-09-18 11:28:00
81 785.8 75 2875 2020-09-18 11:30:00
82 787.45 100 2875 2020-09-18 11:31:00
83 789.9 25 2875 2020-09-18 11:32:00
84 798.1 75 2875 2020-09-18 11:33:00
85 792.85 50 2925 2020-09-18 11:38:00
86 794.2 100 2925 2020-09-18 11:40:00
87 796.55 25 3050 2020-09-18 11:42:00
88 800.0 25 3050 2020-09-18 11:44:00
89 781.9 525 3050 2020-09-18 11:50:00
90 787.85 50 3525 2020-09-18 11:51:00
91 787.15 350 3525 2020-09-18 11:53:00
92 789.0 25 3525 2020-09-18 11:54:00
93 801.9 50 3375 2020-09-18 11:57:00
94 793.3 25 3400 2020-09-18 12:02:00
95 793.4 25 3000 2020-09-18 12:07:00
96 795.0 25 3000 2020-09-18 12:08:00
97 800.95 25 3025 2020-09-18 12:09:00
98 800.9 75 3025 2020-09-18 12:10:00
99 792.85 25 3025 2020-09-18 12:11:00
100 785.3 75 3075 2020-09-18 12:12:00
101 790.8 50 3075 2020-09-18 12:13:00
102 782.0 125 3075 2020-09-18 12:14:00
103 791.9 25 3125 2020-09-18 12:15:00
104 789.9 25 3125 2020-09-18 12:16:00
105 799.65 125 3150 2020-09-18 12:18:00
106 795.15 50 3025 2020-09-18 12:30:00
107 794.05 25 3075 2020-09-18 12:36:00
108 785.75 25 3075 2020-09-18 12:37:00
109 758.5 25 3100 2020-09-18 12:45:00
110 775.0 50 3100 2020-09-18 12:46:00
111 771.6 100 3100 2020-09-18 12:47:00
112 768.6 25 3125 2020-09-18 12:48:00
113 786.95 50 3150 2020-09-18 12:53:00
114 781.5 25 3150 2020-09-18 12:54:00
115 774.95 25 3100 2020-09-18 12:58:00
116 771.7 25 3100 2020-09-18 12:59:00
117 766.7 50 3150 2020-09-18 13:00:00
118 764.55 125 3150 2020-09-18 13:01:00
119 767.0 200 3150 2020-09-18 13:02:00
120 770.0 250 3175 2020-09-18 13:05:00
121 770.15 75 3075 2020-09-18 13:06:00
122 789.15 50 3075 2020-09-18 13:08:00
123 777.7 50 3125 2020-09-18 13:10:00
124 787.0 50 3125 2020-09-18 13:11:00
125 790.0 100 3000 2020-09-18 13:14:00
126 795.0 275 3000 2020-09-18 13:15:00
127 775.0 25 3000 2020-09-18 13:20:00
128 780.0 75 2900 2020-09-18 13:21:00
129 774.15 75 2900 2020-09-18 13:22:00
130 769.0 100 2825 2020-09-18 13:24:00
131 753.2 175 2825 2020-09-18 13:25:00
132 761.7 25 2825 2020-09-18 13:26:00
133 775.0 75 2975 2020-09-18 13:30:00
134 766.15 650 3000 2020-09-18 13:37:00
135 767.5 25 3375 2020-09-18 13:40:00
136 778.0 25 3375 2020-09-18 13:42:00
137 782.0 25 3375 2020-09-18 13:43:00
138 776.5 25 3375 2020-09-18 13:44:00
139 796.1 75 3375 2020-09-18 13:45:00
140 795.2 25 3175 2020-09-18 13:48:00
141 802.55 175 3175 2020-09-18 13:49:00
142 806.3 100 3175 2020-09-18 13:50:00
143 806.65 125 3450 2020-09-18 13:51:00
144 788.2 50 3450 2020-09-18 13:52:00
145 796.25 50 3600 2020-09-18 13:55:00
146 795.0 25 3600 2020-09-18 13:56:00
147 784.4 25 3250 2020-09-18 14:01:00
148 790.0 25 3175 2020-09-18 14:05:00
149 790.0 25 3200 2020-09-18 14:06:00
150 780.0 25 3200 2020-09-18 14:07:00
151 775.0 225 3200 2020-09-18 14:08:00
152 779.0 100 3450 2020-09-18 14:10:00
153 767.0 100 3500 2020-09-18 14:12:00
154 769.0 25 3500 2020-09-18 14:13:00
155 759.7 25 3625 2020-09-18 14:17:00
156 764.45 100 3650 2020-09-18 14:18:00
157 750.0 25 3650 2020-09-18 14:19:00
158 701.9 525 3650 2020-09-18 14:20:00
159 631.0 1725 4050 2020-09-18 14:21:00
160 600.0 275 4050 2020-09-18 14:22:00
161 643.5 500 4050 2020-09-18 14:23:00
162 606.9 475 4275 2020-09-18 14:24:00
163 599.0 1000 4275 2020-09-18 14:25:00
164 590.45 675 4275 2020-09-18 14:26:00
165 605.0 925 4950 2020-09-18 14:27:00
166 614.3 600 4950 2020-09-18 14:28:00
167 600.05 775 4950 2020-09-18 14:29:00
168 595.35 1150 7025 2020-09-18 14:30:00
169 596.2 525 7025 2020-09-18 14:31:00
170 596.8 975 7025 2020-09-18 14:32:00
171 584.0 200 8125 2020-09-18 14:33:00
172 550.0 1750 8125 2020-09-18 14:34:00
173 552.2 1825 8125 2020-09-18 14:35:00
174 554.65 600 8750 2020-09-18 14:36:00
175 565.4 925 8750 2020-09-18 14:37:00
176 565.0 150 8750 2020-09-18 14:38:00
177 583.95 450 9150 2020-09-18 14:39:00
178 561.4 975 9150 2020-09-18 14:40:00
179 566.8 3450 9150 2020-09-18 14:41:00
180 563.35 425 10525 2020-09-18 14:42:00
181 565.4 700 10525 2020-09-18 14:43:00
182 570.0 650 10525 2020-09-18 14:44:00
183 572.8 200 11125 2020-09-18 14:45:00
184 595.25 750 11125 2020-09-18 14:46:00
185 585.75 625 11125 2020-09-18 14:47:00
186 593.4 475 10925 2020-09-18 14:48:00
187 590.0 950 10925 2020-09-18 14:49:00
188 576.4 775 10925 2020-09-18 14:50:00
189 596.55 775 10800 2020-09-18 14:51:00
190 595.95 475 10800 2020-09-18 14:52:00
191 593.95 725 10800 2020-09-18 14:53:00
192 611.45 1500 10550 2020-09-18 14:54:00
193 618.0 1050 10550 2020-09-18 14:55:00
194 600.0 1150 10550 2020-09-18 14:56:00
195 609.15 575 11025 2020-09-18 14:57:00
196 615.6 375 11025 2020-09-18 14:58:00
197 604.4 875 11025 2020-09-18 14:59:00
198 591.3 1225 11375 2020-09-18 15:00:00
199 600.0 1100 11375 2020-09-18 15:01:00
200 597.8 1800 11375 2020-09-18 15:02:00
201 605.0 550 12625 2020-09-18 15:03:00
202 599.1 325 12625 2020-09-18 15:04:00
203 606.2 500 12625 2020-09-18 15:05:00
204 614.65 850 12625 2020-09-18 15:06:00
205 616.0 1225 12625 2020-09-18 15:07:00
206 622.5 1325 12625 2020-09-18 15:08:00
207 620.0 750 13850 2020-09-18 15:09:00
208 632.0 525 13850 2020-09-18 15:10:00
209 630.3 375 13850 2020-09-18 15:11:00
210 635.0 425 13575 2020-09-18 15:12:00
211 630.85 400 13575 2020-09-18 15:13:00
212 627.45 275 13575 2020-09-18 15:14:00
213 620.7 200 13700 2020-09-18 15:15:00
214 622.4 200 13700 2020-09-18 15:16:00
215 631.6 625 13700 2020-09-18 15:17:00
216 624.95 525 13100 2020-09-18 15:18:00
217 632.25 775 13100 2020-09-18 15:19:00
218 610.7 350 13100 2020-09-18 15:20:00
219 602.0 575 13175 2020-09-18 15:21:00
220 612.4 200 13175 2020-09-18 15:22:00
221 617.25 325 13175 2020-09-18 15:23:00
222 617.8 300 13650 2020-09-18 15:24:00
223 622.1 600 13650 2020-09-18 15:25:00
224 622.2 250 13650 2020-09-18 15:26:00
225 623.7 300 13425 2020-09-18 15:27:00
226 622.5 425 13425 2020-09-18 15:28:00
227 621.0 375 13425 2020-09-18 15:29:00
228 567.55 1075 13275 2020-09-21 09:15:00
229 565.0 2100 13275 2020-09-21 09:16:00
230 560.0 1100 14925 2020-09-21 09:17:00
231 562.15 625 14925 2020-09-21 09:18:00
232 556.45 850 14925 2020-09-21 09:19:00
233 543.1 1525 16450 2020-09-21 09:20:00
234 538.0 800 16450 2020-09-21 09:21:00
235 537.45 575 16450 2020-09-21 09:22:00
236 544.4 775 16825 2020-09-21 09:23:00
237 545.7 500 16825 2020-09-21 09:24:00
238 551.4 550 16825 2020-09-21 09:25:00
239 544.25 900 17625 2020-09-21 09:26:00
240 538.0 1850 17625 2020-09-21 09:27:00
241 534.85 525 17625 2020-09-21 09:28:00
242 534.5 425 18775 2020-09-21 09:29:00
243 547.1 1075 18775 2020-09-21 09:30:00
244 536.85 375 18775 2020-09-21 09:31:00
245 547.6 375 19775 2020-09-21 09:32:00
246 540.25 350 19775 2020-09-21 09:33:00
247 541.2 375 19775 2020-09-21 09:34:00
248 544.6 175 18650 2020-09-21 09:35:00
249 542.55 250 18650 2020-09-21 09:36:00
250 539.65 550 18650 2020-09-21 09:37:00
251 531.15 2150 19175 2020-09-21 09:38:00
252 530.1 825 19175 2020-09-21 09:39:00
253 518.7 1575 19175 2020-09-21 09:40:00
254 520.95 575 20475 2020-09-21 09:41:00
255 511.45 1250 20475 2020-09-21 09:42:00
256 517.45 1025 20475 2020-09-21 09:43:00
257 515.0 550 21150 2020-09-21 09:44:00
258 515.0 1125 21150 2020-09-21 09:45:00
259 518.9 425 21150 2020-09-21 09:46:00
260 514.95 550 21500 2020-09-21 09:47:00
261 509.8 1625 21500 2020-09-21 09:48:00
262 507.55 475 21500 2020-09-21 09:49:00
263 514.35 500 21975 2020-09-21 09:50:00
264 524.5 500 21975 2020-09-21 09:51:00
265 527.45 550 21975 2020-09-21 09:52:00
266 527.3 675 21550 2020-09-21 09:53:00
267 521.3 525 21550 2020-09-21 09:54:00
268 520.0 275 21550 2020-09-21 09:55:00
269 519.5 750 21600 2020-09-21 09:56:00
270 516.7 400 21600 2020-09-21 09:57:00
271 517.75 350 21600 2020-09-21 09:58:00
272 511.9 575 21850 2020-09-21 09:59:00
273 507.9 1175 21850 2020-09-21 10:00:00
274 510.05 525 21850 2020-09-21 10:01:00
275 515.85 1025 22350 2020-09-21 10:02:00
276 514.25 600 22350 2020-09-21 10:03:00
277 520.05 650 22350 2020-09-21 10:04:00
278 518.9 950 22850 2020-09-21 10:05:00
279 512.25 550 22850 2020-09-21 10:06:00
280 513.65 650 22850 2020-09-21 10:07:00
281 514.0 525 24300 2020-09-21 10:08:00
282 506.3 875 24300 2020-09-21 10:09:00
283 490.85 1825 24300 2020-09-21 10:10:00
284 499.0 300 25050 2020-09-21 10:11:00
285 495.0 975 25050 2020-09-21 10:12:00
286 497.15 1125 25050 2020-09-21 10:13:00
287 496.8 625 24875 2020-09-21 10:14:00
288 492.95 1075 24875 2020-09-21 10:15:00
289 497.6 1125 24875 2020-09-21 10:16:00
290 502.3 775 24450 2020-09-21 10:17:00
291 501.85 475 24450 2020-09-21 10:18:00
292 502.85 800 24450 2020-09-21 10:19:00
293 511.35 825 24700 2020-09-21 10:20:00
294 537.0 1850 24700 2020-09-21 10:21:00
295 531.55 2025 24700 2020-09-21 10:22:00
296 558.45 2825 24675 2020-09-21 10:23:00
297 555.25 625 24675 2020-09-21 10:24:00
298 577.0 4275 24675 2020-09-21 10:25:00
299 574.0 1075 23500 2020-09-21 10:26:00
300 569.4 600 23500 2020-09-21 10:27:00
I am changing an old question of mine.
I have a file with this format; 4 values per line:
2623 831 6892 0
2353 1803 3425 0
1910 1823 3810 0
1637 1287 2811 0
2803 546 6609 0
1591 2157 2367 0
2167 1906 2665 0
3192 2168 8362 0
3903 1465 2011 0
2355 1801 2004 0
2390 796 5055 0
1703 1044 3441 0
1886 1328 2731 0
1496 1277 3074 0
1827 460 5992 0
1945 1785 2065 0
1983 1963 2818 0
1532 2229 6936 0
2449 5972 1918 0
2699 2007 1581 0
and I want to get this one; 10 values per line:
2623 831 6892 0 2353 1803 3425 0 1910 1823
3810 0 1637 1287 2811 0 2803 546 6609 0
1591 2157 2367 0 2167 1906 2665 0 3192 2168
8362 0 3903 1465 2011 0 2355 1801 2004 0
2390 796 5055 0 1703 1044 3441 0 1886 1328
2731 0 1496 1277 3074 0 1827 460 5992 0
1945 1785 2065 0 1983 1963 2818 0 1532 2229
6936 0 2449 5972 1918 0 2699 2007 1581 0
with open("Read_file") as f1:
with open("Write_file"),"w") as f2:
f2.writelines(itertools.islice(f1, 4, None))
Any tip is appreciated.
Try this:
with open('data.txt') as fp, open('output.txt', 'w') as fw:
data = fp.read().replace('\n', ' ').split()
for i in range(0, len(data) // 10):
fw.write(' '.join(data[i * 10: (i + 1) * 10]) + '\n')
Output:
2623 831 6892 0 2353 1803 3425 0 1910 1823
3810 0 1637 1287 2811 0 2803 546 6609 0
1591 2157 2367 0 2167 1906 2665 0 3192 2168
8362 0 3903 1465 2011 0 2355 1801 2004 0
2390 796 5055 0 1703 1044 3441 0 1886 1328
2731 0 1496 1277 3074 0 1827 460 5992 0
1945 1785 2065 0 1983 1963 2818 0 1532 2229
6936 0 2449 5972 1918 0 2699 2007 1581 0
A version that does not rely on reading the whole file into memory:
def get_words(f):
for line in f:
for word in line.split():
yield word
def chunk_values(iterator, num):
while True:
yield [next(iterator) for _ in range(num)]
with open('input.txt') as fin, open('output.txt', 'w') as fout:
for chunk in chunk_values(get_words(fin), 10):
fout.write(' '.join(chunk) + '\n')
I have the following DataFrame:
Channel Column 1 Column 2 Column 3
Date
12/30/2018 638 4472 487
12/31/2018 868 6985 540
1/1/2019 755 4401 829
1/2/2019 1655 9484 1145
1/3/2019 2002 14212 1158
1/4/2019 1633 9575 1098
1/5/2019 1026 5575 941
1/6/2019 1025 4963 1007
1/7/2019 1944 10685 1246
1/8/2019 2140 9932 1151
1/9/2019 2067 1031 1087
1/10/2019 2168 1005 1074
1/11/2019 2052 9371 909
1/12/2019 1223 5953 895
1/13/2019 1268 4809 827
I would like to return the following result if possible [essentially reduce values between certain dates in a specific column to zero]
Channel Column 1 Column 2 Column 3
Date
12/30/2018 638 4472 487
12/31/2018 868 6985 540
1/1/2019 755 4401 829
1/2/2019 1655 9484 1145
1/3/2019 2002 14212 1158
1/4/2019 1633 9575 1098
1/5/2019 1026 5575 941
1/6/2019 0 4963 1007
1/7/2019 0 10685 1246
1/8/2019 0 9932 1151
1/9/2019 0 1031 1087
1/10/2019 2168 1005 1074
1/11/2019 2052 9371 909
1/12/2019 1223 5953 895
1/13/2019 1268 4809 827
I am trying to filter by a specific column at specific dates, but I can't get it to work properly.
I have tried the following approaches, but I haven't had much luck
df[df['Channel'] == 'Branded Paid Search'].loc['1/6/2019':'1/9/2019']['Sessions'].apply(lambda x: 0 if x < 4000 else 0).to_frame()
This works, but not sure how to get the values back into the original dataframe.
I tried this:
def zero(df):
if df[df['Column 1'] > 0].loc['1/6/2019':'1/9/2019']:
return 0
else:
return 1
df.apply(zero, axis=1)
ValueError: ('The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().')
I tried this:
sessions_df[sessions_df['Column 1'] > 0].loc['1/6/2019':'1/9/2019'] = 0
Nothing changes.
Any help would be appreciated
First create DatetimeIndex by to_datetime and then set values with DataFrame.loc:
df.index = pd.to_datetime(df.index)
df.loc['1/6/2019':'1/9/2019', 'Column 1'] = 0
print (df)
Column 1 Column 2 Column 3
Channel
2018-12-30 638 4472 487
2018-12-31 868 6985 540
2019-01-01 755 4401 829
2019-01-02 1655 9484 1145
2019-01-03 2002 14212 1158
2019-01-04 1633 9575 1098
2019-01-05 1026 5575 941
2019-01-06 0 4963 1007
2019-01-07 0 10685 1246
2019-01-08 0 9932 1151
2019-01-09 0 1031 1087
2019-01-10 2168 1005 1074
2019-01-11 2052 9371 909
2019-01-12 1223 5953 895
2019-01-13 1268 4809 827
I have some marketing data with 1-minute interval.
As a sample of csv-table, each row represents max values for each minute:
time ch1 ch2 ch3 ch4
20:03 1754 539 149 1337
20:04 2073 576 160 1448
20:05 2246 599 176 1515
20:06 2246 637 176 1531
20:07 2457 651 183 1549
20:08 2564 677 184 1655
20:09 2624 712 191 1699
20:10 2742 717 194 1672
20:11 2788 714 199 1675
20:12 2792 693 186 1680
20:13 2914 708 188 1672
20:14 3067 715 194 1685
20:15 3067 725 196 1682
additionally, I need to find max values for each 5 minute. So I need to find max for every 5 rows (or less - if there are no more rows remained) of each columns and insert it to new 5-minute row.
What I looking to recieve (as example):
each new row has to represent max value for 5
time ch1 ch2 ch3 ch4
20:03 2564 677 184 1655
20:08 2914 717 199 1699
20:13 3067 725 196 1685
I honestly have searched but no result.
Is there in Python some elegant solution for my task?
Thank for your help!
g = df.groupby(np.arange(len(df)) // 5)
g.max().assign(time=g.time.first())
time ch1 ch2 ch3 ch4 ch5
0 20:03 2457 651 183 1549 4840
1 20:08 2792 717 199 1699 5376
2 20:13 3067 725 196 1685 5670
By using your input :
df['group']=df.index//5
target=df.groupby('group').agg(max)
target['time']=df.groupby('group').time.agg(min)
Out[511]:
time ch1 ch2 ch3 ch4 ch5
group
0 20:03 2457 651 183 1549 4840
1 20:08 2792 717 199 1699 5376
2 20:13 3067 725 196 1685 5670
Im going to assume that you did not convert your values to datetime since you specified this is a csv table of data, so I will convert the index to datetime.
df.index = pd.to_datetime(df.time,format='%H:%M')
Now that the index is of datetime format we can use resample to group by 5 minute intervals. Note: I will set the base to 3 here since that is how you wanted it formatted, however I think in the long run you may be better suited leaving it at 0. So to group the data just run
df.resample('5T',base=3).max().drop('time',1)
To dynamically set the base to the first minute value use
df.resample('5T',base=int(df.time.values[0][-1:])).max().drop('time',1)
Yields
ch1 ch2 ch3 ch4
time
2017-09-20 20:03:00 2457 651 183 1549
2017-09-20 20:08:00 2792 717 199 1699
2017-09-20 20:13:00 3067 725 196 1685
If you dont want the date in the index just run
df.index = df.index.time
However, you need the date included to resample
ch1 ch2 ch3 ch4
20:03:00 2457 651 183 1549
20:08:00 2792 717 199 1699
20:13:00 3067 725 196 1685