Python 如何使我的功能';输出是否为数据帧?
我已经编写了函数,它给我带来了一些统计数据表。这是:Python 如何使我的功能';输出是否为数据帧?,python,python-3.x,pandas,function,dataframe,Python,Python 3.x,Pandas,Function,Dataframe,我已经编写了函数,它给我带来了一些统计数据表。这是: def demonstrate_best_results(x, features, clusters, indices, cluster_means, differences, rel_differences): for cluster, result in clusters.items(): print( ) print("
def demonstrate_best_results(x, features, clusters, indices,
cluster_means, differences, rel_differences):
for cluster, result in clusters.items():
print( )
print("cluster number : " + str(cluster+1),
"Number of el.", len(indices[cluster] ))
print("grand mean : ",
np.mean(x, axis=0))
print("cluster mean : ", cluster_means[cluster])
print("differences : ", differences[cluster])
print("rel. differences: ", rel_differences[cluster])
当我运行它时:
demonstrate_best_results(x=df, features=df.columns,
clusters=best_clusters_1,
indices=best_indices_1,
cluster_means=best_cluster_means_1,
differences=best_differences_1,
rel_differences=best_rel_differences_1)
我明白了:
cluster number : 1 Number of el. 553
grand mean : [1.14817115e+08 3.85944444e+00 3.68888889e+01 6.59444444e+00]
cluster mean : [9.45822772e+07 4.16365280e+00 3.84918626e+01 3.67450271e+00]
differences : [-2.02348373e+07 3.04208358e-01 1.60297368e+00 -2.91994173e+00]
rel. differences: [-17.62353755 7.88218001 4.34541058 -44.27881312]
cluster number : 2 Number of el. 115
grand mean : [1.14817115e+08 3.85944444e+00 3.68888889e+01 6.59444444e+00]
cluster mean : [1.09844053e+08 4.03913043e+00 3.72000000e+01 2.56608696e+01]
differences : [-4.97306137e+06 1.79685990e-01 3.11111111e-01 1.90664251e+01]
rel. differences: [ -4.33128928 4.65574755 0.84337349 289.12860335]
cluster number : 3 Number of el. 83
grand mean : [1.14817115e+08 3.85944444e+00 3.68888889e+01 6.59444444e+00]
cluster mean : [9.18498693e+07 3.95783133e+00 2.42409639e+01 5.71084337e+00]
differences : [-2.29672452e+07 9.83868809e-02 -1.26479250e+01 -8.83601071e-01]
rel. differences: [-20.00332901 2.54924983 -34.28654377 -13.39917378]
cluster number : 4 Number of el. 127
grand mean : [1.14817115e+08 3.85944444e+00 3.68888889e+01 6.59444444e+00]
cluster mean : [7.23130098e+07 2.30708661e+00 3.79685039e+01 2.72440945e+00]
differences : [-4.25041047e+07 -1.55235783e+00 1.07961505e+00 -3.87003500e+00]
rel. differences: [-37.01896261 -40.22231315 2.9266673 -58.68629311]
cluster number : 5 Number of el. 22
grand mean : [1.14817115e+08 3.85944444e+00 3.68888889e+01 6.59444444e+00]
cluster mean : [9.81456648e+08 3.86363636e+00 3.64545455e+01 6.00000000e+00]
differences : [ 8.66639533e+08 4.19191919e-03 -4.34343434e-01 -5.94444444e-01]
rel. differences: [ 7.54799959e+02 1.08614575e-01 -1.17743702e+00 -9.01432182e+00]
然而,我需要这些表转换成乳胶。那么,如何重写我的函数,以获得熊猫数据框形式的这5个表,以便我可以在之后使用_latex()?您的意思是:
def demonstrate_best_results(x, features, clusters, indices,
cluster_means, differences, rel_differences):
dataframes = []
for cluster, result in clusters.items():
print( )
print("cluster number : " + str(cluster+1),
"Number of el.", len(indices[cluster] ))
df = pd.DataFrame({"grand mean : ": mean(x, axis=0),
"cluster mean : ": cluster_means[cluster],
"differences : ": differences[cluster],
"rel. differences: ", rel_differences[cluster]})
dataframes.append(dataframes)
return dataframes
如何获取这些数据帧?结果如下:集群编号:1个el编号。553集群编号:2个el编号。115集群编号:3个el编号。83集群编号:4个el编号。127簇号:5个el。22出[191]:[…],[…],[…],[…],[…],[…],[…],[…]并且需要让它们在之后应用于_latex()函数并获得一个latex代码,现在如何提取它们?
dataframes=display(…);dataframes[0]。要创建输出数组,请执行以下操作: