我有這個數據集：kaggle：房價：高級回歸技術。我按如下方式加載了它：import numpy as npimport pandas as pdimport matplotlib.pyplot as plt%matplotlib inlineimport seaborn as snsimport scipy.stats as sttrain = pd.read_csv("train.csv")然后，我嘗試使用整體質量作為色調，按年份構建繪制銷售價格：plt.figure(figsize = [8, 6])sns.factorplot( x = 'YearBuilt', y = 'SalePrice', data = train, kind='swarm', hue='OverallQual', palette = 'Set2')plt.title('House Sale Prices (log scale) vs. Year Built and Overall Quality')plt.xticks([1880, 1900, 1920, 1940, 1960, 1980, 2000], ['1880', '1900', '1920', '1940', '1960', '1980', '2000'])#plt.xlim([1872,2009])plt.xlabel('Year Built')plt.yscale('log')#plt.ylim([4e4, 6e5])plt.yticks([6e4, 1e5, 1.4e5, 1.8e5, 2.4e5, 3.2e5, 4e5, 6e5], ['60k', '100k', '140K', '180k', '240K', '320k', '600k'])plt.ylabel('Sale Price ($)')plt.show()結果如下圖所示：如果我包含 xlim 或 ylim，則圖形根本不會顯示出來。我是新手，所以任何幫助都非常感謝。
1 回答
蕪湖不蕪
TA貢獻1796條經驗 獲得超7個贊
plt.style.use('ggplot')
g = sns.catplot(
x = 'YearBuilt',
y = 'SalePrice',
data = train,
kind='swarm',
hue='OverallQual',
palette = 'Set2', height=6, aspect=2)
locs, labels = plt.xticks() # use if needed, as explained below.
for axes in g.axes.flat:
for ind, label in enumerate(axes.get_xticklabels()):
if ind % 8 == 0: # every nth label is kept
label.set_visible(True)
else:
label.set_visible(False)
plt.title('House Sale Prices (log scale) vs. Year Built and Overall Quality')
plt.xlabel('Year Built')
plt.yscale('log')
plt.ylim([4e4, 6e5])
plt.yticks([6e4, 1e5, 1.4e5, 1.8e5, 2.4e5, 3.2e5, 4e5, 6e5], ['60k', '100k', '140K', '180k', '240K', '320k', '600k'])
plt.ylabel('Sale Price ($)')
plt.show()
plt.style.use('ggplot')
g = sns.catplot(
x = 'YearBuilt',
y = 'SalePrice',
data = train,
kind='swarm',
hue='OverallQual',
palette = 'Set2', height=6, aspect=2)
locs, labels = plt.xticks() # use if needed, as explained below.
for axes in g.axes.flat:
for ind, label in enumerate(axes.get_xticklabels()):
if ind % 8 == 0: # every nth label is kept
label.set_visible(True)
else:
label.set_visible(False)
plt.title('House Sale Prices (log scale) vs. Year Built and Overall Quality')
plt.xlabel('Year Built')
plt.yscale('log')
plt.ylim([4e4, 6e5])
plt.yticks([6e4, 1e5, 1.4e5, 1.8e5, 2.4e5, 3.2e5, 4e5, 6e5], ['60k', '100k', '140K', '180k', '240K', '320k', '600k'])
plt.ylabel('Sale Price ($)')
plt.show()
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