{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## import important packages" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from netCDF4 import Dataset\n", "import xarray as xr\n", "import pandas as pd\n", "import cartopy.crs as ccrs\n", "import datetime" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Get sample dataset from Zenodo" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "--2019-10-08 14:56:52-- https://zenodo.org/record/3475894/files/Abisko-prep.tar.gz\n", "Resolving zenodo.org (zenodo.org)... 188.184.65.20\n", "Connecting to zenodo.org (zenodo.org)|188.184.65.20|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 833281373 (795M) [application/octet-stream]\n", "Saving to: ‘Abisko-prep.tar.gz’\n", "\n", "Abisko-prep.tar.gz 100%[===================>] 794.68M 13.3MB/s in 58s \n", "\n", "2019-10-08 14:57:51 (13.7 MB/s) - ‘Abisko-prep.tar.gz’ saved [833281373/833281373]\n", "\n" ] } ], "source": [ "!wget https://zenodo.org/record/3475894/files/Abisko-prep.tar.gz" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Abisko-prep/\n", "Abisko-prep/T_recon_NTREND_NH1_EURO.csv\n", "Abisko-prep/ensmean_temp2_pre_seas_trees_fldmean_a_yrmean.nc\n", "Abisko-prep/Theta_OPT-0015.nc\n", "Abisko-prep/piControl_BOT_1850-2849_temp2_fldmean.nc\n", "Abisko-prep/ue536a02_temp2_pre_seas_trees_fldmean_a_yrmean.nc\n", "Abisko-prep/ue536a04_temp2_pre_seas_trees_fldmean_a_yrmean.nc\n", "Abisko-prep/ensmean_1536_1550_geopoth_seas_a.nc\n", "Abisko-prep/ensmean_PE_seas.nc\n", "Abisko-prep/ue536a01_temp2_pre_seas_trees_fldmean_a_yrmean.nc\n", "Abisko-prep/ue536a06_temp2_pre_seas_trees_fldmean_a_yrmean.nc\n", "Abisko-prep/ue536a05_temp2_pre_seas_trees_fldmean_a_yrmean.nc\n", "Abisko-prep/ue536a03_temp2_pre.nc\n", "Abisko-prep/ue536a03_temp2_pre_seas_trees_fldmean_a_yrmean.nc\n" ] } ], "source": [ "!tar zxvf Abisko-prep.tar.gz" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load a csv file (comma separated values)\n", "- Pandas python package can be used analyze csv \n", "- index_col parameter allows to tell which column in the input file should be \n", " used for indexing the dataset" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "scrolled": true }, "outputs": [], "source": [ "#observations\n", "Stoffel = pd.read_csv('Abisko-prep/T_recon_NTREND_NH1_EURO.csv', index_col='Year')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | EURO_Mean | \n", "Lower2sigma | \n", "Upper2sigma | \n", "Luterbacher 2016 | \n", "MXD/RW/multiproxy | \n", "Year.1 | \n", "NTREND2015 | \n", "upper2sigma | \n", "lower2sigma | \n", "Wilson 2016 | \n", "... | \n", "Unnamed: 24 | \n", "Unnamed: 25 | \n", "Unnamed: 26 | \n", "Unnamed: 27 | \n", "Unnamed: 28 | \n", "Unnamed: 29 | \n", "Unnamed: 30 | \n", "Unnamed: 31 | \n", "Unnamed: 32 | \n", "SSW (Mean=3) | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Year | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
2014 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "Env.Res.Lett | \n", "NaN | \n", "2014.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "QSR | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2013 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2013.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2012 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2012.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2011 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2011.0 | \n", "1.259 | \n", "3.045 | \n", "-0.527 | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2010 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2010.0 | \n", "0.911 | \n", "2.223 | \n", "-0.402 | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
-134 | \n", "-0.503 | \n", "-1.325 | \n", "0.271 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
-135 | \n", "-0.436 | \n", "-1.278 | \n", "0.353 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
-136 | \n", "-0.067 | \n", "-0.916 | \n", "0.750 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
-137 | \n", "-0.029 | \n", "-0.922 | \n", "0.812 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
-138 | \n", "-0.037 | \n", "-0.855 | \n", "0.764 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2152 rows × 33 columns
\n", "