Skip to content

Instantly share code, notes, and snippets.

@wesm

wesm/gist:4328868

Created December 18, 2012 15:17
Show Gist options
  • Save wesm/4328868 to your computer and use it in GitHub Desktop.
Save wesm/4328868 to your computer and use it in GitHub Desktop.
Download ZIP
Long reshaping example from PyData mailing ilst
Raw
gistfile1.txt
{
"metadata": {
"name": "LongReshape"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"from StringIO import StringIO\n",
"pd.set_option('repr_html', False)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data = \"\"\"#QUAD YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL\n",
"0 101 1954 2.77 4.16 6.48 6.55 6.13 6.55 5.03 4.74 3.51 3.80 3.08 2.26 55.07\n",
"1 101 1955 1.65 2.46 5.96 7.15 6.58 8.74 5.27 4.36 4.68 4.82 3.74 2.18 57.58\n",
"2 101 1956 2.46 2.41 5.87 6.32 7.44 5.60 5.75 5.37 5.54 3.35 3.28 1.97 55.36\n",
"3 101 1957 2.45 2.83 4.44 5.01 6.07 4.65 4.58 3.64 3.88 3.05 2.12 2.79 45.52\"\"\"\n",
"\n",
"data = pd.read_table(StringIO(data), delim_whitespace=True)\n",
"data\n",
"idata = data.set_index('#QUAD')\n",
"idata"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 11,
"text": [
" YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ANNUAL\n",
"#QUAD \n",
"101 1954 2.77 4.16 6.48 6.55 6.13 6.55 5.03 4.74 3.51 3.80 3.08 2.26 55.07\n",
"101 1955 1.65 2.46 5.96 7.15 6.58 8.74 5.27 4.36 4.68 4.82 3.74 2.18 57.58\n",
"101 1956 2.46 2.41 5.87 6.32 7.44 5.60 5.75 5.37 5.54 3.35 3.28 1.97 55.36\n",
"101 1957 2.45 2.83 4.44 5.01 6.07 4.65 4.58 3.64 3.88 3.05 2.12 2.79 45.52"
]
}
],
"prompt_number": 11
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mapping = {'evaporation': ['JAN', 'FEB', 'MAR', 'APR', 'MAY', 'JUN', 'JUL',\n",
" 'AUG', 'SEP', 'OCT', 'NOV', 'DEC']}\n",
"quad_data = idata.ix[101]\n",
"result = pd.lreshape(quad_data, mapping)\n",
"result"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 12,
"text": [
" ANNUAL YEAR evaporation\n",
"0 55.07 1954 2.77\n",
"1 57.58 1955 1.65\n",
"2 55.36 1956 2.46\n",
"3 45.52 1957 2.45\n",
"4 55.07 1954 4.16\n",
"5 57.58 1955 2.46\n",
"6 55.36 1956 2.41\n",
"7 45.52 1957 2.83\n",
"8 55.07 1954 6.48\n",
"9 57.58 1955 5.96\n",
"10 55.36 1956 5.87\n",
"11 45.52 1957 4.44\n",
"12 55.07 1954 6.55\n",
"13 57.58 1955 7.15\n",
"14 55.36 1956 6.32\n",
"15 45.52 1957 5.01\n",
"16 55.07 1954 6.13\n",
"17 57.58 1955 6.58\n",
"18 55.36 1956 7.44\n",
"19 45.52 1957 6.07\n",
"20 55.07 1954 6.55\n",
"21 57.58 1955 8.74\n",
"22 55.36 1956 5.60\n",
"23 45.52 1957 4.65\n",
"24 55.07 1954 5.03\n",
"25 57.58 1955 5.27\n",
"26 55.36 1956 5.75\n",
"27 45.52 1957 4.58\n",
"28 55.07 1954 4.74\n",
"29 57.58 1955 4.36\n",
"30 55.36 1956 5.37\n",
"31 45.52 1957 3.64\n",
"32 55.07 1954 3.51\n",
"33 57.58 1955 4.68\n",
"34 55.36 1956 5.54\n",
"35 45.52 1957 3.88\n",
"36 55.07 1954 3.80\n",
"37 57.58 1955 4.82\n",
"38 55.36 1956 3.35\n",
"39 45.52 1957 3.05\n",
"40 55.07 1954 3.08\n",
"41 57.58 1955 3.74\n",
"42 55.36 1956 3.28\n",
"43 45.52 1957 2.12\n",
"44 55.07 1954 2.26\n",
"45 57.58 1955 2.18\n",
"46 55.36 1956 1.97\n",
"47 45.52 1957 2.79"
]
}
],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"result['month'] = np.arange(1, 13).repeat(len(quad_data))\n",
"result"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 14,
"text": [
" ANNUAL YEAR evaporation month\n",
"0 55.07 1954 2.77 1\n",
"1 57.58 1955 1.65 1\n",
"2 55.36 1956 2.46 1\n",
"3 45.52 1957 2.45 1\n",
"4 55.07 1954 4.16 2\n",
"5 57.58 1955 2.46 2\n",
"6 55.36 1956 2.41 2\n",
"7 45.52 1957 2.83 2\n",
"8 55.07 1954 6.48 3\n",
"9 57.58 1955 5.96 3\n",
"10 55.36 1956 5.87 3\n",
"11 45.52 1957 4.44 3\n",
"12 55.07 1954 6.55 4\n",
"13 57.58 1955 7.15 4\n",
"14 55.36 1956 6.32 4\n",
"15 45.52 1957 5.01 4\n",
"16 55.07 1954 6.13 5\n",
"17 57.58 1955 6.58 5\n",
"18 55.36 1956 7.44 5\n",
"19 45.52 1957 6.07 5\n",
"20 55.07 1954 6.55 6\n",
"21 57.58 1955 8.74 6\n",
"22 55.36 1956 5.60 6\n",
"23 45.52 1957 4.65 6\n",
"24 55.07 1954 5.03 7\n",
"25 57.58 1955 5.27 7\n",
"26 55.36 1956 5.75 7\n",
"27 45.52 1957 4.58 7\n",
"28 55.07 1954 4.74 8\n",
"29 57.58 1955 4.36 8\n",
"30 55.36 1956 5.37 8\n",
"31 45.52 1957 3.64 8\n",
"32 55.07 1954 3.51 9\n",
"33 57.58 1955 4.68 9\n",
"34 55.36 1956 5.54 9\n",
"35 45.52 1957 3.88 9\n",
"36 55.07 1954 3.80 10\n",
"37 57.58 1955 4.82 10\n",
"38 55.36 1956 3.35 10\n",
"39 45.52 1957 3.05 10\n",
"40 55.07 1954 3.08 11\n",
"41 57.58 1955 3.74 11\n",
"42 55.36 1956 3.28 11\n",
"43 45.52 1957 2.12 11\n",
"44 55.07 1954 2.26 12\n",
"45 57.58 1955 2.18 12\n",
"46 55.36 1956 1.97 12\n",
"47 45.52 1957 2.79 12"
]
}
],
"prompt_number": 14
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment