```

    import csv
    import pandas as pd
    import numpy as np
    import matplotlib.pyplot as plt
    import seaborn as sns
    %matplotlib inline
    df = pd.read_csv('csv/gaku-mg1712_02_21ver3.csv', encoding='shift_jis',
        parse_dates={'date':['名目時系列']}, index_col='date')
    #gdpDate = df['1994-03-01':'1994-12-01',df['国内総生産']]
    #df['国内総生産']
    #五年ごとの平均と分散によるヒストグラムの作成を行う？？
    
    searchData1 = df.iloc[np.where(('1994-03-01'<= df.index) & (df.index <= '1999-12-01'))]
    searchData2 = df.iloc[np.where(('2000-03-01'<= df.index) & (df.index <= '2004-12-01'))]
    searchData3 = df.iloc[np.where(('2005-03-01'<= df.index) & (df.index <= '2009-12-01'))]
    searchData4 = df.iloc[np.where(('2010-03-01'<= df.index) & (df.index <= '2015-12-01'))]
    sns.set()
    sns.set_context("notebook")
    plt.figure(figsize=(16, 9))
    sns.distplot(searchData1['国内総生産'],
                 hist=False,
                 kde_kws={"color": "k", "lw": 3, "label": "gdp_1995-2000"}, # 凡例の色、線の太さ、名前を記述
                 axlabel='gdp'
                 )
    sns.distplot(searchData2['国内総生産'],
                 hist=False,
                 kde_kws={"color": "b", "lw": 3, "label": "gdp_2000-2005"}, # 凡例の色、線の太さ、名前を記述
                 axlabel='gdp'
                )
    sns.distplot(searchData3['国内総生産'],
                 hist=False,
                 kde_kws={"color": "r", "lw": 3, "label": "gdp_2005-2010"}, # 凡例の色、線の太さ、名前を記述
                 axlabel='gdp')
    sns.distplot(searchData4['国内総生産'],
                 hist=False,
                 kde_kws={"color": "y", "lw": 3, "label": "gdp_2010-2015"}, # 凡例の色、線の太さ、名前を記述
                 axlabel='gdp')
    
```

曲線がはみ出てしまいます。どうしたら改善できますか？  
[![図1.gdpのグラフ](https://i.stack.imgur.com/n9HrR.png)](https://i.stack.imgur.com/n9HrR.png)
CC BY-SA 3.0
2018-02-23T02:58:42.623
41945
2018-09-15T16:21:59.130
2018-09-15T16:21:59.130
19110
27326
question
python python3 matplotlib
seabornのsizeを変更したい
ylimで調整できませんでしたか？

```

    plt.ylim([0.0, 0.0002])
    
```
CC BY-SA 3.0
2018-02-23T04:51:38.863
41950
2018-02-23T04:51:38.863
26311
41945
answer