{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# <center>Pandas Datetime [25 exercises with solution]</center>"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# Importing necessary libraries:\n",
"\n",
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>city</th>\n",
" <th>state/province</th>\n",
" <th>country</th>\n",
" <th>UFO_shape</th>\n",
" <th>length_of_encounter_seconds</th>\n",
" <th>described_duration_of_encounter</th>\n",
" <th>description</th>\n",
" <th>date_documented</th>\n",
" <th>latitude</th>\n",
" <th>longitude</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date_time</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1910-06-01 15:00:00</th>\n",
" <td>wills point</td>\n",
" <td>tx</td>\n",
" <td>us</td>\n",
" <td>cigar</td>\n",
" <td>120</td>\n",
" <td>2 minutes</td>\n",
" <td>Cigar shaped object moving from West to East</td>\n",
" <td>04/16/2005</td>\n",
" <td>32.709167</td>\n",
" <td>-96.008056</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1920-06-11 21:00:00</th>\n",
" <td>cicero</td>\n",
" <td>in</td>\n",
" <td>us</td>\n",
" <td>unknown</td>\n",
" <td>60</td>\n",
" <td>1 minute</td>\n",
" <td>((NUFORC Note: Probable hoax. Note date. PD...</td>\n",
" <td>05/12/2009</td>\n",
" <td>40.123889</td>\n",
" <td>-86.013333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1929-07-05 14:00:00</th>\n",
" <td>buchanan (or burns)</td>\n",
" <td>or</td>\n",
" <td>us</td>\n",
" <td>disk</td>\n",
" <td>60</td>\n",
" <td>1min</td>\n",
" <td>we were traveling east of burns&#44clmbing up ...</td>\n",
" <td>08/16/2002</td>\n",
" <td>43.642500</td>\n",
" <td>-118.627500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1931-06-01 13:00:00</th>\n",
" <td>abilene</td>\n",
" <td>ks</td>\n",
" <td>us</td>\n",
" <td>disk</td>\n",
" <td>1800</td>\n",
" <td>30 min. approx.</td>\n",
" <td>This is a what my mother related to me regardi...</td>\n",
" <td>02/14/2006</td>\n",
" <td>38.917222</td>\n",
" <td>-97.213611</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1939-06-01 20:00:00</th>\n",
" <td>waterloo</td>\n",
" <td>al</td>\n",
" <td>us</td>\n",
" <td>fireball</td>\n",
" <td>300</td>\n",
" <td>5 minutes</td>\n",
" <td>4 high school students see bright&#44 ground-l...</td>\n",
" <td>02/21/2014</td>\n",
" <td>34.918056</td>\n",
" <td>-88.064167</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" city state/province country UFO_shape \\\n",
"Date_time \n",
"1910-06-01 15:00:00 wills point tx us cigar \n",
"1920-06-11 21:00:00 cicero in us unknown \n",
"1929-07-05 14:00:00 buchanan (or burns) or us disk \n",
"1931-06-01 13:00:00 abilene ks us disk \n",
"1939-06-01 20:00:00 waterloo al us fireball \n",
"\n",
" length_of_encounter_seconds \\\n",
"Date_time \n",
"1910-06-01 15:00:00 120 \n",
"1920-06-11 21:00:00 60 \n",
"1929-07-05 14:00:00 60 \n",
"1931-06-01 13:00:00 1800 \n",
"1939-06-01 20:00:00 300 \n",
"\n",
" described_duration_of_encounter \\\n",
"Date_time \n",
"1910-06-01 15:00:00 2 minutes \n",
"1920-06-11 21:00:00 1 minute \n",
"1929-07-05 14:00:00 1min \n",
"1931-06-01 13:00:00 30 min. approx. \n",
"1939-06-01 20:00:00 5 minutes \n",
"\n",
" description \\\n",
"Date_time \n",
"1910-06-01 15:00:00 Cigar shaped object moving from West to East \n",
"1920-06-11 21:00:00 ((NUFORC Note: Probable hoax. Note date. PD... \n",
"1929-07-05 14:00:00 we were traveling east of burns,clmbing up ... \n",
"1931-06-01 13:00:00 This is a what my mother related to me regardi... \n",
"1939-06-01 20:00:00 4 high school students see bright, ground-l... \n",
"\n",
" date_documented latitude longitude \n",
"Date_time \n",
"1910-06-01 15:00:00 04/16/2005 32.709167 -96.008056 \n",
"1920-06-11 21:00:00 05/12/2009 40.123889 -86.013333 \n",
"1929-07-05 14:00:00 08/16/2002 43.642500 -118.627500 \n",
"1931-06-01 13:00:00 02/14/2006 38.917222 -97.213611 \n",
"1939-06-01 20:00:00 02/21/2014 34.918056 -88.064167 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Knowing about the csv file:\n",
"\n",
"ufo_data = pd.read_csv('ufo.csv', index_col = 'Date_time', parse_dates = True)\n",
"ufo_data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 25 Exercises Solutions"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1. Write a Pandas program to create the todays date."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Today's Date-> 2021-02-09\n"
]
}
],
"source": [
"from datetime import date\n",
"\n",
"now = pd.to_datetime(date.today()) # '2019-11-02 00:00:00'\n",
"date = str(now).split()[0] # After split: ['2019-11-02', '00:00:00']\n",
"print('Today\\'s Date->', date)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 2. Write a Pandas program to calculate all the sighting days of the unidentified flying object (ufo) from current date."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Diff in Days\n",
"0 40430\n",
"1 36767\n",
"2 33456\n",
"3 32760\n",
"4 29838\n",
".. ...\n",
"342 6153\n",
"343 5969\n",
"344 5937\n",
"345 5906\n",
"346 6208\n",
"\n",
"[347 rows x 1 columns]\n"
]
}
],
"source": [
"date_diff = (now - ufo_data.index).days # difference of corresponding time in days\n",
"result = date_diff.to_frame(index = False, name='Diff in Days')\n",
"print(result)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3. Write a Pandas program to get the current date, oldest date and number of days between Current date and oldest date of Ufo dataset."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 4. Write a Pandas program to get all the sighting days of the unidentified flying object (ufo) which are less than or equal to 40 years (365*40 days)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 5. Write a Pandas program to get all the sighting days of the unidentified flying object (ufo) between 1950-10-10 and 1960-10-10."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 6. Write a Pandas program to get all the sighting years of the unidentified flying object (ufo) and create the year as column."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 7. Write a Pandas program to create a plot to present the number of unidentified flying object (UFO) reports per year."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 8. Write a Pandas program to extract year, month, day, hour, minute, second and weekday from unidentified flying object (UFO) reporting date."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 9. Write a Pandas program to convert given datetime to timestamp. "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 10. Write a Pandas program to count year-country wise frequency of reporting dates of unidentified flying object(UFO). "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 11. Write a Pandas program to extract unique reporting dates of unidentified flying object (UFO)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 12. Write a Pandas program to get the difference (in days) between documented date and reporting date of unidentified flying object (UFO)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 13. Write a Pandas program to add 100 days with reporting date of unidentified flying object (UFO). "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 14. Write a Pandas program to generate sequences of fixed-frequency dates and time spans."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 15. Write a Pandas program to create a conversion between strings and datetime."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 16. Write a Pandas program to manipulate and convert date times with timezone information."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 17. Write a Pandas program to get the average mean of the UFO (unidentified flying object) sighting was reported."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 18. Write a Pandas program to create a graphical analysis of UFO (unidentified flying object) Sightings year."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 19. Write a Pandas program to check the empty values of UFO (unidentified flying object) Dataframe."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 20. Write a Pandas program to create a plot of distribution of UFO (unidentified flying object) observation time."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 21. Write a Pandas program to create a graphical analysis of UFO (unidentified flying object) sighted by month."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 22. Write a Pandas program to create a comparison of the top 10 years in which the UFO was sighted vs the hours of the day."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 23. Write a Pandas program to create a comparison of the top 10 years in which the UFO was sighted vs each Month."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 24. Write a Pandas program to create a heatmap (rectangular data as a color-encoded matrix) for comparison of the top 10 years in which the UFO was sighted vs each Month. "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 25. Write a Pandas program to create a Timewheel of Hour Vs Year comparison of the top 10 years in which the UFO was sighted."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Data Sources: ufo_sighting_data.csv - [80,332 records] <br>\n",
"Exercises data sources: ufo.csv - [347 random records from ufo_sighting_data.csv] <br>\n",
"\n",
"Note there are no missing data in the columns (ufo.csv).\n",
"\n",
"Source:\n",
"- https://github.com/planetsig/ufo-reports \n",
"- https://www.kaggle.com/camnugent/ufo-sightings-around-the-world"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Reference: [https://www.w3resource.com/python-exercises/pandas/datetime/index.php](https://www.w3resource.com/python-exercises/pandas/datetime/index.php)"
]
}
],
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