使用python 2.7的Kaggle Titanic
import pandas as pd
from pandas import Series,DataFrame
titanic_df = pd.read_csv("train.csv")
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
**sns.factorplot('Pclass',data=titanic_df,hue='Sex')**
获取错误
TypeError Traceback (most recent call last)
<ipython-input-7-a5240a4b6a9f> in <module>()
1 # Let's first check gender
----> 2 sns.factorplot('Sex',data=titanic_df)
C:\Users\bigminduser\Anaconda2\lib\site-packages\seaborn-0.7.0-py2.7.egg\seaborn\categorical.pyc in factorplot(x, y, hue, data, row, col, col_wrap, estimator, ci, n_boot, units, order, hue_order, row_order, col_order, kind, size, aspect, orient, color, palette, legend, legend_out, sharex, sharey, margin_titles, facet_kws, **kwargs)
3365
3366 # Draw the plot onto the facets
-> 3367 g.map_dataframe(plot_func, x, y, hue, **plot_kws)
3368
3369 # Special case axis labels for a count type plot
C:\Users\bigminduser\Anaconda2\lib\site-packages\seaborn-0.7.0-py2.7.egg\seaborn\axisgrid.pyc in map_dataframe(self, func, *args, **kwargs)
791
792 # Draw the plot
--> 793 self._facet_plot(func, ax, args, kwargs)
794
795 # Finalize the annotations and layout
C:\Users\bigminduser\Anaconda2\lib\site-packages\seaborn-0.7.0-py2.7.egg\seaborn\axisgrid.pyc in _facet_plot(self, func, ax, plot_args, plot_kwargs)
809
810 # Draw the plot
--> 811 func(*plot_args, **plot_kwargs)
812
813 # Sort out the supporting information
C:\Users\bigminduser\Anaconda2\lib\site-packages\seaborn-0.7.0-py2.7.egg\seaborn\categorical.pyc in pointplot(x, y, hue, data, order, hue_order, estimator, ci, n_boot, units, markers, linestyles, dodge, join, scale, orient, color, palette, ax, **kwargs)
3009 estimator, ci, n_boot, units,
3010 markers, linestyles, dodge, join, scale,
-> 3011 orient, color, palette)
3012
3013 if ax is None:
C:\Users\bigminduser\Anaconda2\lib\site-packages\seaborn-0.7.0-py2.7.egg\seaborn\categorical.pyc in __init__(self, x, y, hue, data, order, hue_order, estimator, ci, n_boot, units, markers, linestyles, dodge, join, scale, orient, color, palette)
1575 order, hue_order, units)
1576 self.establish_colors(color, palette, 1)
-> 1577 self.estimate_statistic(estimator, ci, n_boot)
1578
1579 # Override the default palette for single-color plots
C:\Users\bigminduser\Anaconda2\lib\site-packages\seaborn-0.7.0-py2.7.egg\seaborn\categorical.pyc in estimate_statistic(self, estimator, ci, n_boot)
1434 statistic.append(np.nan)
1435 else:
-> 1436 statistic.append(estimator(stat_data))
1437
1438 # Get a confidence interval for this estimate
C:\Users\bigminduser\Anaconda2\lib\site-packages\numpy\core\fromnumeric.pyc in mean(a, axis, dtype, out, keepdims)
2872
2873 return _methods._mean(a, axis=axis, dtype=dtype,
-> 2874 out=out, keepdims=keepdims)
2875
2876
C:\Users\bigminduser\Anaconda2\lib\site-packages\numpy\core\_methods.pyc in _mean(a, axis, dtype, out, keepdims)
70 ret = ret.dtype.type(ret / rcount)
71 else:
---> 72 ret = ret / rcount
73
74 return ret
**TypeError: unsupported operand type(s) for /: 'str' and 'long'**
答案 0 :(得分:5)
基于@batmac的答案。在命令中添加import pandas as pd
import seaborn as sns
data = pd.read_csv('train.csv')
sns.factorplot('Sex', data=data, kind="count")
,解决了问题。
示例:强>
{{1}}
答案 1 :(得分:3)