我有一個數據集,我已經設置了250個分區的間隔,並且我有一個非常困難的時間恰當地繪製值。我看了一下使用不均勻分箱繪製分箱數據
python plot simple histogram given binned data
How to make a histogram from a list of data
但對我來說我得到的是一個單一的垂直線。
參考我的離散化的數據是這樣的:
(0, 250] 2
(250, 500] 1
(500, 750] 5
(750, 1000] 13
(1000, 1250] 77
(1250, 1500] 601
(1500, 1750] 1348
(1750, 2000] 3262
(2000, 2250] 3008
(2250, 2500] 5118
(2500, 2750] 4576
(2750, 3000] 5143
(3000, 3250] 3509
(3250, 3500] 4390
(3500, 3750] 2749
(3750, 4000] 2794
(4000, 4250] 1391
(4250, 4500] 1753
(4500, 4750] 1099
(4750, 5000] 1592
(5000, 5250] 688
(5250, 5500] 993
(5500, 5750] 540
(5750, 6000] 937
(6000, 6250] 405
(6250, 6500] 572
(6500, 6750] 202
(6750, 7000] 369
(7000, 7250] 164
(7250, 7500] 231
...
(7750, 8000] 285
(8000, 8250] 55
(8250, 8500] 116
(8500, 8750] 29
(8750, 9000] 140
(9000, 9250] 31
(9250, 9500] 68
(9500, 9750] 20
(9750, 10000] 132
(10000, 10250] 15
(10250, 10500] 29
(10500, 10750] 21
(10750, 11000] 73
(11000, 11250] 26
(11250, 11500] 36
(11500, 11750] 21
(11750, 12000] 74
(12000, 12250] 5
(12250, 12500] 50
(12500, 12750] 13
(12750, 13000] 34
(13000, 13250] 4
(13250, 13500] 45
(13500, 13750] 14
(13750, 14000] 53
(14000, 14250] 6
(14250, 14500] 17
(14500, 14750] 7
(14750, 15000] 79
(15000, 10000000] 256
其中最後一個區間囊括了大於15,000。我已經把上述值在list
然後試圖繪製:
bins = [i for i in range(0, 15001, 250)]
bins.append(10000000)
categories = pd.cut(data["price"], bins)
price_binned = list(pd.value_counts(categories).reindex(categories.cat.categories))
plt.hist(price_binned)
產生12段的直方圖。加入bin
參數
plt.hist(price_binned, bins=(bin_num+1))
產生直方圖從哪裏獲得左側非常高的垂直線。最後,我正在考慮添加plt.xticks(bins)
,但是然後我得到一個什麼都不產生的圖。
無論如何,我可以生成一個直方圖,其中X軸是箱值,Y軸是箱中的值?
使用plt.hist()
使用plt.hist()
與塊沒有倉參數
使用plt.bar()
=倉
使用seaborn
您顯示的數據已經是直方圖。因此,你很難清楚你的目標是什麼。 – ImportanceOfBeingErnest
我想要一個可視化的數據表示,而不是隻將它作爲一個列表 – Lukasz
當然,但是視覺表示中應該不同於已有的直方圖? – ImportanceOfBeingErnest