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/docs/build/html/_static/searchtools.js:
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1 | /*
2 | * searchtools.js_t
3 | * ~~~~~~~~~~~~~~~~
4 | *
5 | * Sphinx JavaScript utilities for the full-text search.
6 | *
7 | * :copyright: Copyright 2007-2017 by the Sphinx team, see AUTHORS.
8 | * :license: BSD, see LICENSE for details.
9 | *
10 | */
11 |
12 |
13 | /* Non-minified version JS is _stemmer.js if file is provided */
14 | /**
15 | * Porter Stemmer
16 | */
17 | var Stemmer = function() {
18 |
19 | var step2list = {
20 | ational: 'ate',
21 | tional: 'tion',
22 | enci: 'ence',
23 | anci: 'ance',
24 | izer: 'ize',
25 | bli: 'ble',
26 | alli: 'al',
27 | entli: 'ent',
28 | eli: 'e',
29 | ousli: 'ous',
30 | ization: 'ize',
31 | ation: 'ate',
32 | ator: 'ate',
33 | alism: 'al',
34 | iveness: 'ive',
35 | fulness: 'ful',
36 | ousness: 'ous',
37 | aliti: 'al',
38 | iviti: 'ive',
39 | biliti: 'ble',
40 | logi: 'log'
41 | };
42 |
43 | var step3list = {
44 | icate: 'ic',
45 | ative: '',
46 | alize: 'al',
47 | iciti: 'ic',
48 | ical: 'ic',
49 | ful: '',
50 | ness: ''
51 | };
52 |
53 | var c = "[^aeiou]"; // consonant
54 | var v = "[aeiouy]"; // vowel
55 | var C = c + "[^aeiouy]*"; // consonant sequence
56 | var V = v + "[aeiou]*"; // vowel sequence
57 |
58 | var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0
59 | var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1
60 | var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1
61 | var s_v = "^(" + C + ")?" + v; // vowel in stem
62 |
63 | this.stemWord = function (w) {
64 | var stem;
65 | var suffix;
66 | var firstch;
67 | var origword = w;
68 |
69 | if (w.length < 3)
70 | return w;
71 |
72 | var re;
73 | var re2;
74 | var re3;
75 | var re4;
76 |
77 | firstch = w.substr(0,1);
78 | if (firstch == "y")
79 | w = firstch.toUpperCase() + w.substr(1);
80 |
81 | // Step 1a
82 | re = /^(.+?)(ss|i)es$/;
83 | re2 = /^(.+?)([^s])s$/;
84 |
85 | if (re.test(w))
86 | w = w.replace(re,"$1$2");
87 | else if (re2.test(w))
88 | w = w.replace(re2,"$1$2");
89 |
90 | // Step 1b
91 | re = /^(.+?)eed$/;
92 | re2 = /^(.+?)(ed|ing)$/;
93 | if (re.test(w)) {
94 | var fp = re.exec(w);
95 | re = new RegExp(mgr0);
96 | if (re.test(fp[1])) {
97 | re = /.$/;
98 | w = w.replace(re,"");
99 | }
100 | }
101 | else if (re2.test(w)) {
102 | var fp = re2.exec(w);
103 | stem = fp[1];
104 | re2 = new RegExp(s_v);
105 | if (re2.test(stem)) {
106 | w = stem;
107 | re2 = /(at|bl|iz)$/;
108 | re3 = new RegExp("([^aeiouylsz])\\1$");
109 | re4 = new RegExp("^" + C + v + "[^aeiouwxy]$");
110 | if (re2.test(w))
111 | w = w + "e";
112 | else if (re3.test(w)) {
113 | re = /.$/;
114 | w = w.replace(re,"");
115 | }
116 | else if (re4.test(w))
117 | w = w + "e";
118 | }
119 | }
120 |
121 | // Step 1c
122 | re = /^(.+?)y$/;
123 | if (re.test(w)) {
124 | var fp = re.exec(w);
125 | stem = fp[1];
126 | re = new RegExp(s_v);
127 | if (re.test(stem))
128 | w = stem + "i";
129 | }
130 |
131 | // Step 2
132 | re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
133 | if (re.test(w)) {
134 | var fp = re.exec(w);
135 | stem = fp[1];
136 | suffix = fp[2];
137 | re = new RegExp(mgr0);
138 | if (re.test(stem))
139 | w = stem + step2list[suffix];
140 | }
141 |
142 | // Step 3
143 | re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
144 | if (re.test(w)) {
145 | var fp = re.exec(w);
146 | stem = fp[1];
147 | suffix = fp[2];
148 | re = new RegExp(mgr0);
149 | if (re.test(stem))
150 | w = stem + step3list[suffix];
151 | }
152 |
153 | // Step 4
154 | re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
155 | re2 = /^(.+?)(s|t)(ion)$/;
156 | if (re.test(w)) {
157 | var fp = re.exec(w);
158 | stem = fp[1];
159 | re = new RegExp(mgr1);
160 | if (re.test(stem))
161 | w = stem;
162 | }
163 | else if (re2.test(w)) {
164 | var fp = re2.exec(w);
165 | stem = fp[1] + fp[2];
166 | re2 = new RegExp(mgr1);
167 | if (re2.test(stem))
168 | w = stem;
169 | }
170 |
171 | // Step 5
172 | re = /^(.+?)e$/;
173 | if (re.test(w)) {
174 | var fp = re.exec(w);
175 | stem = fp[1];
176 | re = new RegExp(mgr1);
177 | re2 = new RegExp(meq1);
178 | re3 = new RegExp("^" + C + v + "[^aeiouwxy]$");
179 | if (re.test(stem) || (re2.test(stem) && !(re3.test(stem))))
180 | w = stem;
181 | }
182 | re = /ll$/;
183 | re2 = new RegExp(mgr1);
184 | if (re.test(w) && re2.test(w)) {
185 | re = /.$/;
186 | w = w.replace(re,"");
187 | }
188 |
189 | // and turn initial Y back to y
190 | if (firstch == "y")
191 | w = firstch.toLowerCase() + w.substr(1);
192 | return w;
193 | }
194 | }
195 |
196 |
197 |
198 | /**
199 | * Simple result scoring code.
200 | */
201 | var Scorer = {
202 | // Implement the following function to further tweak the score for each result
203 | // The function takes a result array [filename, title, anchor, descr, score]
204 | // and returns the new score.
205 | /*
206 | score: function(result) {
207 | return result[4];
208 | },
209 | */
210 |
211 | // query matches the full name of an object
212 | objNameMatch: 11,
213 | // or matches in the last dotted part of the object name
214 | objPartialMatch: 6,
215 | // Additive scores depending on the priority of the object
216 | objPrio: {0: 15, // used to be importantResults
217 | 1: 5, // used to be objectResults
218 | 2: -5}, // used to be unimportantResults
219 | // Used when the priority is not in the mapping.
220 | objPrioDefault: 0,
221 |
222 | // query found in title
223 | title: 15,
224 | // query found in terms
225 | term: 5
226 | };
227 |
228 |
229 |
230 |
231 |
232 | var splitChars = (function() {
233 | var result = {};
234 | var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648,
235 | 1748, 1809, 2416, 2473, 2481, 2526, 2601, 2609, 2612, 2615, 2653, 2702,
236 | 2706, 2729, 2737, 2740, 2857, 2865, 2868, 2910, 2928, 2948, 2961, 2971,
237 | 2973, 3085, 3089, 3113, 3124, 3213, 3217, 3241, 3252, 3295, 3341, 3345,
238 | 3369, 3506, 3516, 3633, 3715, 3721, 3736, 3744, 3748, 3750, 3756, 3761,
239 | 3781, 3912, 4239, 4347, 4681, 4695, 4697, 4745, 4785, 4799, 4801, 4823,
240 | 4881, 5760, 5901, 5997, 6313, 7405, 8024, 8026, 8028, 8030, 8117, 8125,
241 | 8133, 8181, 8468, 8485, 8487, 8489, 8494, 8527, 11311, 11359, 11687, 11695,
242 | 11703, 11711, 11719, 11727, 11735, 12448, 12539, 43010, 43014, 43019, 43587,
243 | 43696, 43713, 64286, 64297, 64311, 64317, 64319, 64322, 64325, 65141];
244 | var i, j, start, end;
245 | for (i = 0; i < singles.length; i++) {
246 | result[singles[i]] = true;
247 | }
248 | var ranges = [[0, 47], [58, 64], [91, 94], [123, 169], [171, 177], [182, 184], [706, 709],
249 | [722, 735], [741, 747], [751, 879], [888, 889], [894, 901], [1154, 1161],
250 | [1318, 1328], [1367, 1368], [1370, 1376], [1416, 1487], [1515, 1519], [1523, 1568],
251 | [1611, 1631], [1642, 1645], [1750, 1764], [1767, 1773], [1789, 1790], [1792, 1807],
252 | [1840, 1868], [1958, 1968], [1970, 1983], [2027, 2035], [2038, 2041], [2043, 2047],
253 | [2070, 2073], [2075, 2083], [2085, 2087], [2089, 2307], [2362, 2364], [2366, 2383],
254 | [2385, 2391], [2402, 2405], [2419, 2424], [2432, 2436], [2445, 2446], [2449, 2450],
255 | [2483, 2485], [2490, 2492], [2494, 2509], [2511, 2523], [2530, 2533], [2546, 2547],
256 | [2554, 2564], [2571, 2574], [2577, 2578], [2618, 2648], [2655, 2661], [2672, 2673],
257 | [2677, 2692], [2746, 2748], [2750, 2767], [2769, 2783], [2786, 2789], [2800, 2820],
258 | [2829, 2830], [2833, 2834], [2874, 2876], [2878, 2907], [2914, 2917], [2930, 2946],
259 | [2955, 2957], [2966, 2968], [2976, 2978], [2981, 2983], [2987, 2989], [3002, 3023],
260 | [3025, 3045], [3059, 3076], [3130, 3132], [3134, 3159], [3162, 3167], [3170, 3173],
261 | [3184, 3191], [3199, 3204], [3258, 3260], [3262, 3293], [3298, 3301], [3312, 3332],
262 | [3386, 3388], [3390, 3423], [3426, 3429], [3446, 3449], [3456, 3460], [3479, 3481],
263 | [3518, 3519], [3527, 3584], [3636, 3647], [3655, 3663], [3674, 3712], [3717, 3718],
264 | [3723, 3724], [3726, 3731], [3752, 3753], [3764, 3772], [3774, 3775], [3783, 3791],
265 | [3802, 3803], [3806, 3839], [3841, 3871], [3892, 3903], [3949, 3975], [3980, 4095],
266 | [4139, 4158], [4170, 4175], [4182, 4185], [4190, 4192], [4194, 4196], [4199, 4205],
267 | [4209, 4212], [4226, 4237], [4250, 4255], [4294, 4303], [4349, 4351], [4686, 4687],
268 | [4702, 4703], [4750, 4751], [4790, 4791], [4806, 4807], [4886, 4887], [4955, 4968],
269 | [4989, 4991], [5008, 5023], [5109, 5120], [5741, 5742], [5787, 5791], [5867, 5869],
270 | [5873, 5887], [5906, 5919], [5938, 5951], [5970, 5983], [6001, 6015], [6068, 6102],
271 | [6104, 6107], [6109, 6111], [6122, 6127], [6138, 6159], [6170, 6175], [6264, 6271],
272 | [6315, 6319], [6390, 6399], [6429, 6469], [6510, 6511], [6517, 6527], [6572, 6592],
273 | [6600, 6607], [6619, 6655], [6679, 6687], [6741, 6783], [6794, 6799], [6810, 6822],
274 | [6824, 6916], [6964, 6980], [6988, 6991], [7002, 7042], [7073, 7085], [7098, 7167],
275 | [7204, 7231], [7242, 7244], [7294, 7400], [7410, 7423], [7616, 7679], [7958, 7959],
276 | [7966, 7967], [8006, 8007], [8014, 8015], [8062, 8063], [8127, 8129], [8141, 8143],
277 | [8148, 8149], [8156, 8159], [8173, 8177], [8189, 8303], [8306, 8307], [8314, 8318],
278 | [8330, 8335], [8341, 8449], [8451, 8454], [8456, 8457], [8470, 8472], [8478, 8483],
279 | [8506, 8507], [8512, 8516], [8522, 8525], [8586, 9311], [9372, 9449], [9472, 10101],
280 | [10132, 11263], [11493, 11498], [11503, 11516], [11518, 11519], [11558, 11567],
281 | [11622, 11630], [11632, 11647], [11671, 11679], [11743, 11822], [11824, 12292],
282 | [12296, 12320], [12330, 12336], [12342, 12343], [12349, 12352], [12439, 12444],
283 | [12544, 12548], [12590, 12592], [12687, 12689], [12694, 12703], [12728, 12783],
284 | [12800, 12831], [12842, 12880], [12896, 12927], [12938, 12976], [12992, 13311],
285 | [19894, 19967], [40908, 40959], [42125, 42191], [42238, 42239], [42509, 42511],
286 | [42540, 42559], [42592, 42593], [42607, 42622], [42648, 42655], [42736, 42774],
287 | [42784, 42785], [42889, 42890], [42893, 43002], [43043, 43055], [43062, 43071],
288 | [43124, 43137], [43188, 43215], [43226, 43249], [43256, 43258], [43260, 43263],
289 | [43302, 43311], [43335, 43359], [43389, 43395], [43443, 43470], [43482, 43519],
290 | [43561, 43583], [43596, 43599], [43610, 43615], [43639, 43641], [43643, 43647],
291 | [43698, 43700], [43703, 43704], [43710, 43711], [43715, 43738], [43742, 43967],
292 | [44003, 44015], [44026, 44031], [55204, 55215], [55239, 55242], [55292, 55295],
293 | [57344, 63743], [64046, 64047], [64110, 64111], [64218, 64255], [64263, 64274],
294 | [64280, 64284], [64434, 64466], [64830, 64847], [64912, 64913], [64968, 65007],
295 | [65020, 65135], [65277, 65295], [65306, 65312], [65339, 65344], [65371, 65381],
296 | [65471, 65473], [65480, 65481], [65488, 65489], [65496, 65497]];
297 | for (i = 0; i < ranges.length; i++) {
298 | start = ranges[i][0];
299 | end = ranges[i][1];
300 | for (j = start; j <= end; j++) {
301 | result[j] = true;
302 | }
303 | }
304 | return result;
305 | })();
306 |
307 | function splitQuery(query) {
308 | var result = [];
309 | var start = -1;
310 | for (var i = 0; i < query.length; i++) {
311 | if (splitChars[query.charCodeAt(i)]) {
312 | if (start !== -1) {
313 | result.push(query.slice(start, i));
314 | start = -1;
315 | }
316 | } else if (start === -1) {
317 | start = i;
318 | }
319 | }
320 | if (start !== -1) {
321 | result.push(query.slice(start));
322 | }
323 | return result;
324 | }
325 |
326 |
327 |
328 |
329 | /**
330 | * Search Module
331 | */
332 | var Search = {
333 |
334 | _index : null,
335 | _queued_query : null,
336 | _pulse_status : -1,
337 |
338 | init : function() {
339 | var params = $.getQueryParameters();
340 | if (params.q) {
341 | var query = params.q[0];
342 | $('input[name="q"]')[0].value = query;
343 | this.performSearch(query);
344 | }
345 | },
346 |
347 | loadIndex : function(url) {
348 | $.ajax({type: "GET", url: url, data: null,
349 | dataType: "script", cache: true,
350 | complete: function(jqxhr, textstatus) {
351 | if (textstatus != "success") {
352 | document.getElementById("searchindexloader").src = url;
353 | }
354 | }});
355 | },
356 |
357 | setIndex : function(index) {
358 | var q;
359 | this._index = index;
360 | if ((q = this._queued_query) !== null) {
361 | this._queued_query = null;
362 | Search.query(q);
363 | }
364 | },
365 |
366 | hasIndex : function() {
367 | return this._index !== null;
368 | },
369 |
370 | deferQuery : function(query) {
371 | this._queued_query = query;
372 | },
373 |
374 | stopPulse : function() {
375 | this._pulse_status = 0;
376 | },
377 |
378 | startPulse : function() {
379 | if (this._pulse_status >= 0)
380 | return;
381 | function pulse() {
382 | var i;
383 | Search._pulse_status = (Search._pulse_status + 1) % 4;
384 | var dotString = '';
385 | for (i = 0; i < Search._pulse_status; i++)
386 | dotString += '.';
387 | Search.dots.text(dotString);
388 | if (Search._pulse_status > -1)
389 | window.setTimeout(pulse, 500);
390 | }
391 | pulse();
392 | },
393 |
394 | /**
395 | * perform a search for something (or wait until index is loaded)
396 | */
397 | performSearch : function(query) {
398 | // create the required interface elements
399 | this.out = $('#search-results');
400 | this.title = $('
41 |
373 |
409 |
410 |
42 |
372 |
43 |
44 |
371 |
45 |
49 | Welcome to pyspark_histogram’s documentation!¶
46 |
47 |
48 |
50 |
368 |
369 |
370 | Indices and tables¶
51 |-
52 |
- Index 53 |
- Module Index 54 |
- Search Page 55 |
57 |
367 | Documentation for the Code¶
58 |-
59 |
-
60 |
pyspark_dist_explore.hist(axis, x, overlapping=False, formatted_yaxis=True, **kwargs)[source]¶
61 | Plots a histogram on an Axis object
62 |-
63 |
- Args: 64 |
65 |
93 |66 | 67 | 68 | axis: (Axes) 69 | An matplotlib Axes object on which the histogram will be plot.
70 |x: (DataFrame or list of DataFrame) 73 | A DataFrame with one or more numerical columns, or a list of single numerical column DataFrames
74 |overlapping: (bool, optional) 77 | Generate overlapping histograms.
78 |If set to true, this will generate an overlapping plot. 79 | When set to False it will generate a normal grouped histogram. Defaults to False.
80 |formatted_yaxis: (bool, optional) 84 | If set to true, the numbers on the yaxis will be formatted 85 | for better readability. E.g. 1500000 will become 1.5M. Defaults to True
86 |**kwargs: The keyword arguments as used in matplotlib.pyplot.hist
89 |
94 | - Returns: 95 |
96 |
116 |97 | 98 | 99 | n: (array or list of arrays) 100 | The values of the histogram bins. See normed and weights for a description of the possible semantics. 101 | If input x is an array, then this is an array of length nbins. If input is a sequence arrays 102 | [data1, data2,..], then this is a list of arrays with the values of the histograms for each of the 103 | arrays in the same order. 104 |bins: (array) 106 | The edges of the bins. 107 | Length nbins + 1 (nbins left edges and right edge of last bin). Always a single array even 108 | when multiple data sets are passed in. 109 |patches: (list or list of lists) 111 | Silent list of individual patches used to create the histogram or list of such lists if multiple 112 | input datasets. 113 |
117 |
-
121 |
-
122 |
pyspark_dist_explore.distplot(axis, x, **kwargs)[source]¶
123 | Plots a normalised histogram and a density plot on an Axes object
124 |-
125 |
- Args: 126 |
127 |
140 |128 | 129 | 130 | axis: (Axes) 131 | An matplotlib Axes object on which the histogram will be plot. 132 |x: (DataFrame or list of DataFrame) 134 | A DataFrame with one or more numerical columns, or a list of single numerical column DataFrames 135 |**kwargs: The keyword arguments as used in matplotlib.pyplot.hist. Normed is set to True 137 |
141 | - Returns: 142 |
143 |
163 |144 | 145 | 146 | n: (array or list of arrays) 147 | The values of the histogram bins. See normed and weights for a description of the possible semantics. 148 | If input x is an array, then this is an array of length nbins. If input is a sequence arrays 149 | [data1, data2,..], then this is a list of arrays with the values of the histograms for each of the 150 | arrays in the same order. 151 |bins: (array) 153 | The edges of the bins. 154 | Length nbins + 1 (nbins left edges and right edge of last bin). Always a single array even 155 | when multiple data sets are passed in. 156 |patches: (list or list of lists) 158 | Silent list of individual patches used to create the histogram or list of such lists if multiple 159 | input datasets. 160 |
164 |
-
168 |
-
169 |
pyspark_dist_explore.pandas_histogram(x, bins=10, range=None)[source]¶
170 | Returns a pandas DataFrame with histograms of the Spark DataFrame
171 |Bin ranges are formatted as text an put on the Index.
172 |-
173 |
- Args: 174 |
175 |
199 |176 | 177 | 178 | x: (DataFrame or list of DataFrame) 179 | A DataFrame with one or more numerical columns, or a list of single numerical column DataFrames
180 |bins: (integer or array_like, optional) 183 | If an integer is given, bins + 1 bin edges are returned, consistently with numpy.histogram() for 184 | numpy version >= 1.3.
185 |Unequally spaced bins are supported if bins is a sequence.
186 |Default is 10
187 |range: (tuple or None, optional) 190 | The lower and upper range of the bins. Lower and upper outliers are ignored. 191 | If not provided, range is (x.min(), x.max()). Range has no effect if bins is a sequence.
192 |If bins is a sequence or range is specified, autoscaling is based on the specified bin range instead 193 | of the range of x.
194 |Default is None
195 |
200 |
-
204 |
-
205 | class
pyspark_dist_explore.Histogram(bins=10, range=None)[source]¶
206 | The Histogram object leverages Spark to calculate histograms, and matplotlib to visualize these.
207 |-
208 |
- Args: 209 |
210 |
227 |211 | 212 | 213 | range: (tuple, optional) 214 | The lower and upper range of the bins. 215 | Lower and upper outliers are ignored. If not provided, range is (min(x), max(x)). Range has no 216 | effect if bins is a sequence. If bins is a sequence or range is specified, autoscaling is 217 | based on the specified bin range instead of the range of x. 218 |bins: (int or list of str or list of `int, optional) 220 | If an integer is given: Number of bins in the histogram. Defaults to 10. 221 | If a list is given: Predefined list of bin boundaries. 222 | The bins are all open to the right except for the last which is closed. e.g. [1,10,20,50] means 223 | the buckets are [1,10) [10,20) [20,50], which means 1<=x<10, 10<=x<20, 20<=x<=50. 224 |
228 |
-
230 |
-
231 |
add_column(table)[source]¶
232 | Add single column DataFrame to the histogram object.
233 |If multiple columns share the same name, a (n) will be appended to the name, where n is 234 | the next available number.
235 |-
236 |
- Args: 237 |
238 |
246 |239 | 240 | 241 | table: ( 243 |dataframe) 242 | A PySpark DataFrame with a single column
247 |
-
251 |
-
252 |
add_data(data)[source]¶
253 | Ads 1 or more columns to a histogram.
254 |-
255 |
- Multiple options are available: 256 |
-
257 |
- Add a single column dataframe 258 |
- Add a list of single column dataframes 259 |
- Add a dataframe with multiple columns 260 |
262 | - Args: 263 |
264 |
272 |265 | 266 | 267 | data: A single column Spark dataframe, a list of single column Spark 268 | dataframes, or a multi column Spark dataframe. 269 |
273 |
-
277 |
-
278 |
build()[source]¶
279 | Calculates the histogram values for each of the columns.
280 |If the Histogram has already been build, it doesn’t build it again.
281 |
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284 |
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285 |
plot_density(ax, num=300, **kwargs)[source]¶
286 | Returns a density plot on an Pyplot Axes object.
287 |-
288 |
- Args: 289 |
290 |
303 |291 | 292 | 293 | ax: (Axes) 294 | An matplotlib Axes object on which the histogram will be plot 295 |num: (int) 297 | The number of x values the line is plotted on. Default: 300 298 |**kwargs: Keyword arguments that are passed on to the pyplot.plot function. 300 |
304 |
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308 |
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309 |
plot_hist(ax, overlapping=False, formatted_yaxis=True, **kwargs)[source]¶
310 | Returns a matplotlib style histogram (matplotlib.pyplot.hist)
311 |Uses the matplotlib object oriented interface to add a Histogram to an matplotlib Axes object. 312 | All named arguments from pyplot.hist can be used. A new argument called “type” makes it possible to 313 | make overlapping histogram plots.
314 |-
315 |
- Args: 316 |
317 |
336 |318 | 319 | 320 | ax: (Axes) 321 | An matplotlib Axes object on which the histogram will be plot 322 |overlapping (bool, optional): If set to true, this will generate an overlapping plot. 325 | When set to False it will generate a normal grouped histogram. Defaults to False. 326 |formatted_yaxis: (bool, optional). 329 | If set to true, the numbers on the yaxis will be formatted 330 | for better readability. E.g. 1500000 will become 1.5M. Defaults to True 331 |**kwargs: The keyword arguments as used in matplotlib.pyplot.hist 333 |
337 |
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341 |
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342 |
to_pandas(kind='hist')[source]¶
343 | Returns a pandas dataframe from the Histogram object.
344 |This function calculates the Histogram function in Spark if it was not done yet.
345 |-
346 |
- Args: 347 |
348 |
358 |349 | 350 | 351 | kind: ( 355 |str, optional): 352 | ‘hist’ or ‘density’. When using hist this returns the histogram object 353 | as pandas dataframe. When using density the index contains the bin centers, and the values in the 354 | DataFrame are the scaled values. Defaults to ‘hist’
359 | - Returns: 360 |
- A pandas DataFrame from the Histogram object. 361 |
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