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Created March 13, 2023 19:36
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Data School's Tuesday Tip #7
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{
"cells": [
{
"cell_type": "markdown",
"id": "fb685b42",
"metadata": {},
"source": [
"## [Tuesday Tip #7](https://tuesday.tips/): Time zones and Daylight Savings Time in pandas"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "869919ba",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "markdown",
"id": "dd80c5b3",
"metadata": {},
"source": [
"[List of offset aliases](https://pandas.pydata.org/docs/user_guide/timeseries.html#timeseries-offset-aliases) (such as \"H\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a888cdd3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 2023-03-12 04:00:00\n",
"1 2023-03-12 05:00:00\n",
"2 2023-03-12 06:00:00\n",
"3 2023-03-12 07:00:00\n",
"4 2023-03-12 08:00:00\n",
"5 2023-03-12 09:00:00\n",
"dtype: datetime64[ns]"
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},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"times = pd.Series(pd.date_range(start='2023-03-12 4:00', periods=6, freq='H'))\n",
"times"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "33f98c8e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 2023-03-12 04:00:00+00:00\n",
"1 2023-03-12 05:00:00+00:00\n",
"2 2023-03-12 06:00:00+00:00\n",
"3 2023-03-12 07:00:00+00:00\n",
"4 2023-03-12 08:00:00+00:00\n",
"5 2023-03-12 09:00:00+00:00\n",
"dtype: datetime64[ns, UTC]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"UTC_times = times.dt.tz_localize('UTC')\n",
"UTC_times"
]
},
{
"cell_type": "markdown",
"id": "e221ee76",
"metadata": {},
"source": [
"[List of time zones](https://en.wikipedia.org/wiki/List_of_tz_database_time_zones) (such as \"America/New_York\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "107d60e7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 2023-03-11 23:00:00-05:00\n",
"1 2023-03-12 00:00:00-05:00\n",
"2 2023-03-12 01:00:00-05:00\n",
"3 2023-03-12 03:00:00-04:00\n",
"4 2023-03-12 04:00:00-04:00\n",
"5 2023-03-12 05:00:00-04:00\n",
"dtype: datetime64[ns, America/New_York]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"UTC_times.dt.tz_convert('America/New_York')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "003d4346",
"metadata": {},
"outputs": [],
"source": [
"times = pd.Series(pd.date_range(start='2023-11-05 3:00', periods=6, freq='H'))"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "34163f28",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 2023-11-04 23:00:00-04:00\n",
"1 2023-11-05 00:00:00-04:00\n",
"2 2023-11-05 01:00:00-04:00\n",
"3 2023-11-05 01:00:00-05:00\n",
"4 2023-11-05 02:00:00-05:00\n",
"5 2023-11-05 03:00:00-05:00\n",
"dtype: datetime64[ns, America/New_York]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"times.dt.tz_localize('UTC').dt.tz_convert('America/New_York')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
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"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
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