mirror of
https://github.com/donnemartin/data-science-ipython-notebooks.git
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360 lines
6.0 KiB
Plaintext
360 lines
6.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<small><i>This notebook was prepared by [Donne Martin](http://donnemartin.com). Source and license info is on [GitHub](https://github.com/donnemartin/data-science-ipython-notebooks).</i></small>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Dates and Times"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* Basics\n",
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"* strftime\n",
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"* strptime\n",
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"* timedelta"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Basics"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"from datetime import datetime, date, time"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"year = 2015\n",
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"month = 1\n",
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"day = 20\n",
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"hour = 7\n",
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"minute = 28\n",
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"second = 15"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"dt = datetime(year, month, day, hour, minute, second)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(7, 28, 15)"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"dt.hour, dt.minute, dt.second"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Extract the equivalent date object:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"datetime.date(2015, 1, 20)"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"dt.date()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Extract the equivalent time object:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"datetime.time(7, 28, 15)"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"dt.time()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"When aggregating or grouping time series data, it is sometimes useful to replace fields of a series of datetimes such as zeroing out the minute and second fields:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"datetime.datetime(2015, 1, 20, 7, 0)"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"dt.replace(minute=0, second=0)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## strftime"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Format a datetime string:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'01/20/2015 07:28'"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"dt.strftime('%m/%d/%Y %H:%M')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## strptime"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Convert a string into a datetime object:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"datetime.datetime(2015, 1, 20, 0, 0)"
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]
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},
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"datetime.strptime('20150120', '%Y%m%d')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## timedelta"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Get the current datetime:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"dt_now = datetime.now()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Subtract two datetime fields to create a timedelta:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"datetime.timedelta(6, 40171, 885211)"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"delta = dt_now - dt\n",
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"delta"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Add a datetime and a timedelta to get a new datetime:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"datetime.datetime(2015, 1, 26, 18, 37, 46, 885211)"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"dt + delta"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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