如何用月份绘制x轴？

Question

I want to plot a dataframe df1 . The x axis contains month and the y-axis counts. My x axis is just a black bar because of too many values. I tried a lot but nothing works. Is there a simple way to plot just every 5th date for example? I think the problem is that the month are date times and I can't build the minimum and maximum? 

df1 = pd.read_csv('hello.csv')

plt.plot(df1['a'],df1['b'])
plt.show()

My data frame df1 is:

a       b
2006-06,211.0
2006-07,212.41176470588235
2006-08,238.26315789473685
2006-09,239.9375
2006-10,266.1111111111111
2006-11,265.22222222222223
2006-12,283.3333333333333
2007-01,290.0
2007-02,307.5
2007-03,325.0
2007-04,343.05882352941177
2007-05,340.42105263157896
2007-06,353.75
2007-07,348.5
2007-08,359.6111111111111
2007-09,346.5625
2007-10,365.57894736842104
2007-11,358.7647058823529
2007-12,372.8333333333333
2008-01,381.8888888888889
2008-02,396.25
2008-03,422.94117647058823
2008-04,428.6666666666667
2008-05,418.5882352941176
2008-06,433.0
2008-07,440.4736842105263
2008-08,470.375
2008-09,481.3529411764706
2008-10,489.44444444444446
2008-11,485.125
2008-12,514.5714285714286
2009-01,515.375
2009-02,535.3125
2009-03,555.0555555555555
2009-04,557.7222222222222
2009-05,533.375
2009-06,567.7222222222222
2009-07,575.1111111111111
2009-08,582.5294117647059
2009-09,569.1666666666666
2009-10,611.1176470588235
2009-11,591.6470588235294
2009-12,634.6428571428571
2010-01,647.9375
2010-02,655.375
2010-03,672.7368421052631
2010-04,678.5882352941177
2010-05,667.8235294117648
2010-06,689.5
2010-07,657.4117647058823
2010-08,679.1111111111111
2010-09,661.2222222222222
2010-10,685.75
2010-11,676.5555555555555
2010-12,692.3571428571429
2011-01,691.9411764705883
2011-02,697.4375
2011-03,720.5263157894736
2011-04,723.5
2011-05,694.7222222222222
2011-06,705.7222222222222
2011-07,677.9375
2011-08,693.7368421052631
2011-09,671.2352941176471
2011-10,685.1176470588235
2011-11,669.9444444444445
2011-12,708.3076923076923
2012-01,674.9444444444445
2012-04,748.0
2012-05,811.0526315789474
2012-06,863.6875
2012-07,843.1666666666666
2012-08,885.5
2012-09,857.75
2012-10,876.8421052631579
2012-11,863.1764705882352
2012-12,917.6666666666666
2013-01,933.4444444444445
2013-03,975.0625
2013-04,994.0
2013-05,1019.6666666666666
2013-06,1063.625
2013-07,1057.8947368421052
2013-08,1102.1764705882354
2013-09,1046.4117647058824
2013-10,1153.1052631578948
2013-11,1107.25
2013-12,1155.3076923076924
2014-01,1191.3529411764705
2014-02,1240.5
2014-03,1272.764705882353
2014-04,1316.9444444444443
2014-05,1310.3529411764705
2014-06,1349.4117647058824
2014-07,1403.8947368421052
2014-08,1412.375
2014-09,1409.0555555555557
2014-10,1472.9444444444443
2014-11,1421.8125
2014-12,1473.2142857142858
2015-01,1476.9375
2015-02,1495.75
2015-03,1546.111111111111
2015-04,1563.7777777777778
2015-05,1499.0
2015-06,1583.111111111111
2015-07,1594.2222222222222
2015-08,1618.1176470588234
2015-09,1595.8333333333333
2015-10,1706.3529411764705
2015-11,1652.8823529411766
2015-12,1691.0714285714287
2016-01,1717.125
2016-02,1746.7058823529412
2016-03,1945.4736842105262
2016-04,2329.375
2016-05,2408.4444444444443
2016-06,2404.222222222222
2016-07,2184.4375
2016-08,2160.6315789473683
2016-09,2402.176470588235
2016-10,2481.823529411765
2016-11,2372.0
2016-12,2153.0
2017-01,2145.777777777778
2017-02,2213.5625
2017-03,2309.6111111111113
2017-04,2295.8125
2017-05,2116.7894736842104
2017-06,2093.8823529411766

Answer 1

In order to show every nth value, what you can do is to set the x-ticks value.

x = df1['a']
plt.xticks(np.arange(0, len(x), 1.0)) #you can replace 1 with the step interval

Or else, what you can do to further improve the visibility and keep the accuracy is to rotate the x axis inputs by modifying the x-ticks with a rotation variable.

import matplotlib.pyplot as plt


x = [1, 2, 3, 4]
y = [1, 4, 9, 6]
labels = ['Frogs', 'Hogs', 'Bogs', 'Slogs']

plt.plot(x, y)
# You can specify a rotation for the tick labels in degrees or with keywords.
plt.xticks(x, labels, rotation='vertical') # You can input an integer too.
# Pad margins so that markers don't get clipped by the axes
plt.margins(0.2)
# Tweak spacing to prevent clipping of tick-labels
plt.subplots_adjust(bottom=0.15)
plt.show()