Pandas Datetime: Add 100 days with reporting date of unidentified flying object (UFO)
Write a Pandas program to add 100 days with reporting date of unidentified flying object (UFO).
Sample Solution :
Python Code :
import pandas as pd
from datetime import timedelta
df = pd.read_csv(r'ufo.csv')
df['Date_time'] = df['Date_time'].astype('datetime64[ns]')
print("Original Dataframe:")
print(df.head())
print("\nAdd 100 days with reporting date:")
df['New_doc_dt'] = df['Date_time'] + timedelta(days=180)
print(df)
Sample Output:
Original Dataframe:
Date_time city ... latitude longitude
0 1910-06-01 15:00:00 wills point ... 32.709167 -96.008056
1 1920-06-11 21:00:00 cicero ... 40.123889 -86.013333
2 1929-07-05 14:00:00 buchanan (or burns) ... 43.642500 -118.627500
3 1931-06-01 13:00:00 abilene ... 38.917222 -97.213611
4 1939-06-01 20:00:00 waterloo ... 34.918056 -88.064167
[5 rows x 11 columns]
Add 100 days with reporting date:
Date_time ... New_doc_dt
0 1910-06-01 15:00:00 ... 1910-11-28 15:00:00
1 1920-06-11 21:00:00 ... 1920-12-08 21:00:00
2 1929-07-05 14:00:00 ... 1930-01-01 14:00:00
3 1931-06-01 13:00:00 ... 1931-11-28 13:00:00
4 1939-06-01 20:00:00 ... 1939-11-28 20:00:00
5 1939-07-07 02:00:00 ... 1940-01-03 02:00:00
6 1941-06-01 13:00:00 ... 1941-11-28 13:00:00
7 1942-06-01 22:30:00 ... 1942-11-28 22:30:00
8 1944-01-01 12:00:00 ... 1944-06-29 12:00:00
9 1944-06-01 12:00:00 ... 1944-11-28 12:00:00
10 1944-04-02 11:00:00 ... 1944-09-29 11:00:00
11 1945-06-01 13:30:00 ... 1945-11-28 13:30:00
12 1945-06-07 07:00:00 ... 1945-12-04 07:00:00
13 1945-08-08 12:00:00 ... 1946-02-04 12:00:00
14 1945-07-10 01:30:00 ... 1946-01-06 01:30:00
15 1946-02-01 17:00:00 ... 1946-07-31 17:00:00
16 1946-07-01 13:30:00 ... 1946-12-28 13:30:00
17 1946-01-08 02:00:00 ... 1946-07-07 02:00:00
18 1947-06-01 02:30:00 ... 1947-11-28 02:30:00
19 1947-06-01 17:00:00 ... 1947-11-28 17:00:00
20 1947-07-01 20:00:00 ... 1947-12-28 20:00:00
21 1947-07-01 20:00:00 ... 1947-12-28 20:00:00
22 1948-08-01 02:00:00 ... 1949-01-28 02:00:00
23 1948-05-10 19:00:00 ... 1948-11-06 19:00:00
24 1948-12-12 23:30:00 ... 1949-06-10 23:30:00
25 1949-05-01 14:00:00 ... 1949-10-28 14:00:00
26 1949-07-01 11:00:00 ... 1949-12-28 11:00:00
27 1949-07-01 16:00:00 ... 1949-12-28 16:00:00
28 1949-04-10 15:00:00 ... 1949-10-07 15:00:00
29 1950-06-01 16:00:00 ... 1950-11-28 16:00:00
.. ... ... ...
317 2002-03-01 06:15:00 ... 2002-08-28 06:15:00
318 2002-08-01 15:25:00 ... 2003-01-28 15:25:00
319 2002-01-02 17:30:00 ... 2002-07-01 17:30:00
320 2002-07-03 01:00:00 ... 2002-12-30 01:00:00
321 2002-07-04 20:23:00 ... 2002-12-31 20:23:00
322 2002-09-05 23:00:00 ... 2003-03-04 23:00:00
323 2002-10-05 23:00:00 ... 2003-04-03 23:00:00
324 2002-05-06 15:50:00 ... 2002-11-02 15:50:00
325 2002-01-07 18:00:00 ... 2002-07-06 18:00:00
326 2002-09-08 16:00:00 ... 2003-03-07 16:00:00
327 2002-05-09 18:00:00 ... 2002-11-05 18:00:00
328 2002-05-10 23:30:00 ... 2002-11-06 23:30:00
329 2002-01-11 18:45:00 ... 2002-07-10 18:45:00
330 2002-02-12 20:00:00 ... 2002-08-11 20:00:00
331 2003-04-01 01:00:00 ... 2003-09-28 01:00:00
332 2003-10-02 02:45:00 ... 2004-03-30 02:45:00
333 2003-11-04 20:00:00 ... 2004-05-02 20:00:00
334 2003-01-06 10:10:00 ... 2003-07-05 10:10:00
335 2003-05-07 02:00:00 ... 2003-11-03 02:00:00
336 2003-07-08 00:30:00 ... 2004-01-04 00:30:00
337 2003-04-09 21:00:00 ... 2003-10-06 21:00:00
338 2003-03-10 20:52:00 ... 2003-09-06 20:52:00
339 2003-07-11 20:50:00 ... 2004-01-07 20:50:00
340 2004-02-01 01:00:00 ... 2004-07-30 01:00:00
341 2004-10-02 18:20:00 ... 2005-03-31 18:20:00
342 2004-04-05 20:35:00 ... 2004-10-02 20:35:00
343 2004-10-06 23:00:00 ... 2005-04-04 23:00:00
344 2004-11-07 20:30:00 ... 2005-05-06 20:30:00
345 2004-12-08 05:30:00 ... 2005-06-06 05:30:00
346 2004-02-10 05:15:00 ... 2004-08-08 05:15:00
[347 rows x 12 columns]
Python Code Editor:
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