diff --git a/notebooks/c05_Big_Data/Working_with_Big_Data.ipynb b/notebooks/c05_Big_Data/Working_with_Big_Data.ipynb index 904bc2a..b0c8b0a 100644 --- a/notebooks/c05_Big_Data/Working_with_Big_Data.ipynb +++ b/notebooks/c05_Big_Data/Working_with_Big_Data.ipynb @@ -82,9 +82,21 @@ " pid = os.getpid()\n", " mem_bytes = psutil.Process(pid).memory_info().rss\n", " print('[Process {} uses {:.1f}MB]'.format(pid, mem_bytes / 1024 / 1024))\n", - " return mem_bytes / 1024 / 1024\n" + " return mem_bytes / 1024 / 1024" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-10-04T05:48:45.857630Z", + "start_time": "2020-10-04T05:48:45.846756Z" + } + }, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": 4, @@ -501,8 +513,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-10-04T05:48:45.857630Z", - "start_time": "2020-10-04T05:48:45.846756Z" + "end_time": "2020-10-04T06:40:44.790440Z", + "start_time": "2020-10-04T06:40:43.466984Z" } }, "outputs": [], @@ -784,12 +796,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-10-04T06:40:44.790440Z", - "start_time": "2020-10-04T06:40:43.466984Z" - } - }, + "metadata": {}, "outputs": [], "source": [] }, @@ -2257,6 +2264,2025 @@ "" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Xarray\n", + "\n", + "Xarray is pandas for N-dimensional data. It also has a [dask backend](http://xarray.pydata.org/en/stable/dask.html)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "ExecuteTime": { + "end_time": "2020-10-12T08:10:18.705068Z", + "start_time": "2020-10-12T08:10:18.539317Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "\n", + "Dimensions: (x: 275, y: 205)\n", + "Coordinates:\n", + " time object 1981-07-17 00:00:00\n", + " xc (y, x) float64 dask.array\n", + " yc (y, x) float64 dask.array\n", + "Dimensions without coordinates: x, y\n", + "Data variables:\n", + " Tair (y, x) float64 dask.array\n", + "Attributes:\n", + " title: /workspace/jhamman/processed/R1002RBRxaaa01a/l...\n", + " institution: U.W.\n", + " source: RACM R1002RBRxaaa01a\n", + " output_frequency: daily\n", + " output_mode: averaged\n", + " convention: CF-1.4\n", + " references: Based on the initial model of Liang et al., 19...\n", + " comment: Output from the Variable Infiltration Capacity...\n", + " nco_openmp_thread_number: 1\n", + " NCO: netCDF Operators version 4.7.9 (Homepage = htt...\n", + " history: Fri Aug 7 17:57:38 2020: ncatted -a bounds,,d..." + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# You can use isel instead of iloc. You always need to specify the dimension\n", + "ds.isel(time=10)['Tair'].plot.pcolormesh(\n", + " vmin=-30, vmax=30, cmap='Spectral_r',\n", + " add_colorbar=True, extend='both')\n", + "\n", + "ds.isel(time=10)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": { + "ExecuteTime": { + "end_time": "2020-10-12T08:14:04.619997Z", + "start_time": "2020-10-12T08:14:04.542987Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.DataArray 'Tair' (time: 4)>\n",
+       "dask.array<getitem, shape=(4,), dtype=float64, chunksize=(1,), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * time     (time) object 1980-12-31 00:00:00 ... 1983-12-31 00:00:00\n",
+       "    xc       float64 dask.array<chunksize=(), meta=np.ndarray>\n",
+       "    yc       float64 dask.array<chunksize=(), meta=np.ndarray>
" + ], + "text/plain": [ + "\n", + "dask.array\n", + "Coordinates:\n", + " * time (time) object 1980-12-31 00:00:00 ... 1983-12-31 00:00:00\n", + " xc float64 dask.array\n", + " yc float64 dask.array" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# You can also resample by date\n", + "res = ds.resample(time='A').mean().isel(x=200, y=200)['Tair']\n", + "# The result is a dask array\n", + "res" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "ExecuteTime": { + "end_time": "2020-10-12T08:14:13.932955Z", + "start_time": "2020-10-12T08:14:13.880801Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/wassname/.pyenv/versions/jup3.7.3/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", + " x = np.divide(x1, x2, out)\n" + ] + }, + { + "data": { + "text/html": [ + "
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<xarray.DataArray 'Tair' (time: 4)>\n",
+       "array([ 6.75662201,  8.97479849, 10.49235584,  9.59892096])\n",
+       "Coordinates:\n",
+       "  * time     (time) object 1980-12-31 00:00:00 ... 1983-12-31 00:00:00\n",
+       "    xc       float64 42.47\n",
+       "    yc       float64 44.82
" + ], + "text/plain": [ + "\n", + "array([ 6.75662201, 8.97479849, 10.49235584, 9.59892096])\n", + "Coordinates:\n", + " * time (time) object 1980-12-31 00:00:00 ... 1983-12-31 00:00:00\n", + " xc float64 42.47\n", + " yc float64 44.82" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# But you can use .compute\n", + "res.compute()" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/notebooks/c05_Big_Data/Working_with_Big_Data.py b/notebooks/c05_Big_Data/Working_with_Big_Data.py index e663302..6331c08 100644 --- a/notebooks/c05_Big_Data/Working_with_Big_Data.py +++ b/notebooks/c05_Big_Data/Working_with_Big_Data.py @@ -523,6 +523,37 @@ def can_compile(x): # # +# # Xarray +# +# Xarray is pandas for N-dimensional data. It also has a [dask backend](http://xarray.pydata.org/en/stable/dask.html) + +# + +# %matplotlib inline +import numpy as np +import pandas as pd +import xarray as xr +import matplotlib.pyplot as plt + +ds = xr.tutorial.open_dataset('rasm').load().chunk(dict(time=10)) +ds + +# + +# You can use isel instead of iloc. You always need to specify the dimension +ds.isel(time=10)['Tair'].plot.pcolormesh( + vmin=-30, vmax=30, cmap='Spectral_r', + add_colorbar=True, extend='both') + +ds.isel(time=10) +# - + +# You can also resample by date +res = ds.resample(time='A').mean().isel(x=200, y=200)['Tair'] +# The result is a dask array +res + +# But you can use .compute +res.compute() + # # References # The following sources where used for creation of this notebook: # - https://github.com/NCAR/ncar-python-tutorial