pandas, scikit-learn, xgboost and seaborn integration

Related tags

Machine Learningpandas-ml
Overview

pandas-ml

Latest Docs https://travis-ci.org/pandas-ml/pandas-ml.svg?branch=master

Overview

pandas, scikit-learn and xgboost integration.

Installation

$ pip install pandas_ml

Documentation

http://pandas-ml.readthedocs.org/en/stable/

Example

>>> import pandas_ml as pdml
>>> import sklearn.datasets as datasets

# create ModelFrame instance from sklearn.datasets
>>> df = pdml.ModelFrame(datasets.load_digits())
>>> type(df)
<class 'pandas_ml.core.frame.ModelFrame'>

# binarize data (features), not touching target
>>> df.data = df.data.preprocessing.binarize()
>>> df.head()
   .target  0  1  2  3  4  5  6  7  8 ...  54  55  56  57  58  59  60  61  62  63
0        0  0  0  1  1  1  1  0  0  0 ...   0   0   0   0   1   1   1   0   0   0
1        1  0  0  0  1  1  1  0  0  0 ...   0   0   0   0   0   1   1   1   0   0
2        2  0  0  0  1  1  1  0  0  0 ...   1   0   0   0   0   1   1   1   1   0
3        3  0  0  1  1  1  1  0  0  0 ...   1   0   0   0   1   1   1   1   0   0
4        4  0  0  0  1  1  0  0  0  0 ...   0   0   0   0   0   1   1   1   0   0
[5 rows x 65 columns]

# split to training and test data
>>> train_df, test_df = df.model_selection.train_test_split()

# create estimator (accessor is mapped to sklearn namespace)
>>> estimator = df.svm.LinearSVC()

# fit to training data
>>> train_df.fit(estimator)

# predict test data
>>> test_df.predict(estimator)
0     4
1     2
2     7
...
448    5
449    8
Length: 450, dtype: int64

# Evaluate the result
>>> test_df.metrics.confusion_matrix()
Predicted   0   1   2   3   4   5   6   7   8   9
Target
0          52   0   0   0   0   0   0   0   0   0
1           0  37   1   0   0   1   0   0   3   3
2           0   2  48   1   0   0   0   1   1   0
3           1   1   0  44   0   1   0   0   3   1
4           1   0   0   0  43   0   1   0   0   0
5           0   1   0   0   0  39   0   0   0   0
6           0   1   0   0   1   0  35   0   0   0
7           0   0   0   0   2   0   0  42   1   0
8           0   2   1   0   1   0   0   0  33   1
9           0   2   1   2   0   0   0   0   1  38

Supported Packages

  • scikit-learn
  • patsy
  • xgboost
Comments
  • Fixed imports of deprecated modules which were removed in pandas 0.24.0

    Fixed imports of deprecated modules which were removed in pandas 0.24.0

    Certain functions were deprecated in a previous version of pandas and moved to a different module (see #117). This PR fixes the imports of those functions.

    opened by kristofve 8
  • REL: v0.4.0

    REL: v0.4.0

    • [x] Compat/test for sklearn 0.18.0 (#81)
      • [x] initial fix (#81)
      • [x] wrapper for cross validation classes (re-enable skipped tests) (#85)
      • [x] tests for multioutput (#86)
      • [x] Update doc
    • [x] Compat/test for pandas 0.19.0 (#83)
    • [x] Update release note (#88)
    opened by sinhrks 4
  • Importation error

    Importation error

    I tried to import pandas_ml but it gave the error :

    AttributeError: type object 'NDFrame' has no attribute 'groupby'

    I'm running python3.8.1 and I installed pandas_ml via pip (version 20.0.2)

    I dig in the code, error is l.80 of file series.py

    @Appender(pd.core.generic.NDFrame.groupby.__doc__)

    Here pandas is imported at the top of the file with a classic import pandas as pd

    I guess there is a problem with the versions...

    Thanks in advance for any help

    opened by ierezell 2
  • Confusion Matrix no accessible

    Confusion Matrix no accessible

    Hi,

    I've been using confusion_matrix since it was an independent package. I've installed pandas_ml to continue using the package, but it seems that the setup.py script does not install the package.

    Could it be an issue with the find_packages function?

    opened by mmartinortiz 2
  • Seaborn Scatterplot matrix / pairplot integration

    Seaborn Scatterplot matrix / pairplot integration 

    import seaborn as sns
sns.set()

df = sns.load_dataset("iris")
sns.pairplot(df, hue="species")

    displays

    iris_scatter_matrix

    but pairplot doesn't work the same way with ModelFrame

    import pandas as pd
pd.set_option('max_rows', 10)
import sklearn.datasets as datasets
import pandas_ml as pdml  # https://github.com/pandas-ml/pandas-ml
import seaborn as sns
import matplotlib.pyplot as plt
df = pdml.ModelFrame(datasets.load_iris())
sns.pairplot(df, hue=".target")

    iris_modelframe

    There is some useless subplots

    opened by scls19fr 2
  • Error while running train.py from speech commands in tensorflow examples.

    Error while running train.py from speech commands in tensorflow examples.

    Have the following error: File "train.py", line 27, in <module> from callbacks import ConfusionMatrixCallback File "/home/tesseract/ayush_workspace/NLP/WakeWord/tensorflow_trainer/ml/callbacks.py", line 21, in <module> from pandas_ml import ConfusionMatrix File "/home/tesseract/anaconda3/envs/ciao/lib/python3.6/site-packages/pandas_ml/__init__.py", line 3, in <module> from pandas_ml.core import ModelFrame, ModelSeries # noqa File "/home/tesseract/anaconda3/envs/ciao/lib/python3.6/site-packages/pandas_ml/core/__init__.py", line 3, in <module> from pandas_ml.core.frame import ModelFrame # noqa File "/home/tesseract/anaconda3/envs/ciao/lib/python3.6/site-packages/pandas_ml/core/frame.py", line 18, in <module> from pandas_ml.core.series import ModelSeries File "/home/tesseract/anaconda3/envs/ciao/lib/python3.6/site-packages/pandas_ml/core/series.py", line 11, in <module> class ModelSeries(ModelTransformer, pd.Series): File "/home/tesseract/anaconda3/envs/ciao/lib/python3.6/site-packages/pandas_ml/core/series.py", line 80, in ModelSeries @Appender(pd.core.generic.NDFrame.groupby.__doc__) AttributeError: type object 'NDFrame' has no attribute 'groupby' Happening with both version 5 and 6.1

    opened by ayush7 1
  • error for example https://pandas-ml.readthedocs.io/en/latest/xgboost.html

    error for example https://pandas-ml.readthedocs.io/en/latest/xgboost.html

    code from example https://pandas-ml.readthedocs.io/en/latest/xgboost.html '''import pandas_ml as pdml import sklearn.datasets as datasets df = pdml.ModelFrame(datasets.load_digits()) train_df, test_df = df.cross_validation.train_test_split() estimator = df.xgboost.XGBClassifier() train_df.fit(estimator) predicted = test_df.predict(estimator) q=1 test_df.metrics.confusion_matrix() train_df.xgboost.plot_importance()

    tuned_parameters = [{'max_depth': [3, 4]}] cv = df.grid_search.GridSearchCV(df.xgb.XGBClassifier(), tuned_parameters, cv=5)

    df.fit(cv) df.grid_search.describe(cv) q=1

    '''

    gives error ''' File "E:\Pandas\my_code\S_pandas_ml_feb27.py", line 10, in train_df.xgboost.plot_importance() File "C:\Users\sndr\Anaconda3\Lib\site-packages\pandas_ml\xgboost\base.py", line 61, in plot_importance return xgb.plot_importance(self._df.estimator.booster(),

    builtins.TypeError: 'str' object is not callable ''' I use Windows and 3.6.4 |Anaconda, Inc.| (default, Jan 16 2018, 10:22:32) [MSC v.1900 64 bit (AMD64)] Python Type "help", "copyright", "credits" or "license" for more information.

    opened by Sandy4321 1
  • pandas 0.24.0 has deprecated pandas.util.decorators

    pandas 0.24.0 has deprecated pandas.util.decorators

    See https://pandas.pydata.org/pandas-docs/stable/whatsnew/v0.24.0.html#deprecations

    This causes the import statement in https://github.com/pandas-ml/pandas-ml/blob/master/pandas_ml/core/frame.py to break.

    Looks like just need to change it to 'from pandas.utils'

    opened by usul83 1
  • 'mean_absoloute_error

    'mean_absoloute_error

    from sklearn import metrics print('MAE:',metrics.mean_absoloute_error(y_test,y_pred)) module 'sklearn.metrics' has no attribute 'mean_absoloute_error This error is occurred..any solution

    opened by vikramk1507 0
  • AttributeError: type object 'NDFrame' has no attribute 'groupby'

    AttributeError: type object 'NDFrame' has no attribute 'groupby'

    AttributeError: type object 'NDFrame' has no attribute 'groupby'

    from pandas_ml import ConfusionMatrix cm = ConfusionMatrix(actu, pred) cm.print_stats()

    AttributeError Traceback (most recent call last) in ----> 1 from pandas_ml import confusion_matrix 2 3 cm = ConfusionMatrix(actu, pred) 4 cm.print_stats()

    /usr/local/lib/python3.8/site-packages/pandas_ml/init.py in 1 #!/usr/bin/env python 2 ----> 3 from pandas_ml.core import ModelFrame, ModelSeries # noqa 4 from pandas_ml.tools import info # noqa 5 from pandas_ml.version import version as version # noqa

    /usr/local/lib/python3.8/site-packages/pandas_ml/core/init.py in 1 #!/usr/bin/env python 2 ----> 3 from pandas_ml.core.frame import ModelFrame # noqa 4 from pandas_ml.core.series import ModelSeries # noqa

    /usr/local/lib/python3.8/site-packages/pandas_ml/core/frame.py in 16 from pandas_ml.core.accessor import _AccessorMethods 17 from pandas_ml.core.generic import ModelPredictor, _shared_docs ---> 18 from pandas_ml.core.series import ModelSeries 19 20

    /usr/local/lib/python3.8/site-packages/pandas_ml/core/series.py in 9 10 ---> 11 class ModelSeries(ModelTransformer, pd.Series): 12 """ 13 Wrapper for pandas.Series to support sklearn.preprocessing

    /usr/local/lib/python3.8/site-packages/pandas_ml/core/series.py in ModelSeries() 78 return df 79 ---> 80 @Appender(pd.core.generic.NDFrame.groupby.doc) 81 def groupby(self, by=None, axis=0, level=None, as_index=True, sort=True, 82 group_keys=True, squeeze=False):

    AttributeError: type object 'NDFrame' has no attribute 'groupby'

    opened by gfranco008 5
  • AttributeError: module 'sklearn.metrics' has no attribute 'jaccard_similarity_score'

    AttributeError: module 'sklearn.metrics' has no attribute 'jaccard_similarity_score'

    I am using scikit-learn version 0.23.1 and I get the following error: AttributeError: module 'sklearn.metrics' has no attribute 'jaccard_similarity_score' when calling the function ConfusionMatrix.

    opened by petraknovak 11
  • Error while running train.py from speech commands in tensorflow examples. AttributeError: type object 'NDFrame' has no attribute 'groupby'

    Error while running train.py from speech commands in tensorflow examples. AttributeError: type object 'NDFrame' has no attribute 'groupby'

    Have the following error: File "train.py", line 27, in <module> from callbacks import ConfusionMatrixCallback File "/home/tesseract/ayush_workspace/NLP/WakeWord/tensorflow_trainer/ml/callbacks.py", line 21, in <module> from pandas_ml import ConfusionMatrix File "/home/tesseract/anaconda3/envs/ciao/lib/python3.6/site-packages/pandas_ml/__init__.py", line 3, in <module> from pandas_ml.core import ModelFrame, ModelSeries # noqa File "/home/tesseract/anaconda3/envs/ciao/lib/python3.6/site-packages/pandas_ml/core/__init__.py", line 3, in <module> from pandas_ml.core.frame import ModelFrame # noqa File "/home/tesseract/anaconda3/envs/ciao/lib/python3.6/site-packages/pandas_ml/core/frame.py", line 18, in <module> from pandas_ml.core.series import ModelSeries File "/home/tesseract/anaconda3/envs/ciao/lib/python3.6/site-packages/pandas_ml/core/series.py", line 11, in <module> class ModelSeries(ModelTransformer, pd.Series): File "/home/tesseract/anaconda3/envs/ciao/lib/python3.6/site-packages/pandas_ml/core/series.py", line 80, in ModelSeries @Appender(pd.core.generic.NDFrame.groupby.__doc__) AttributeError: type object 'NDFrame' has no attribute 'groupby' Happening with both version 5 and 6.1

    opened by ayush7 3
  • Pandas 1.0.0rc0/0.6.1 module 'sklearn.preprocessing' has no attribute 'Imputer'

    Pandas 1.0.0rc0/0.6.1 module 'sklearn.preprocessing' has no attribute 'Imputer'

    SKLEARN

    sklearn.preprocessing.Imputer Warning DEPRECATED

    class sklearn.preprocessing.Imputer(*args, **kwargs)[source] Imputation transformer for completing missing values.

    Read more in the User Guide.

    
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-1-e0471065d85c> in <module>
      1 import pandas as pd
      2 import numpy as np
----> 3 import pandas_ml as pdml
      4 a1 = np.random.randint(0,2,size=(100,2))
      5 df = pd.DataFrame(a1,columns=['i1','i2'])

C:\g\test\lib\pandas_ml\__init__.py in <module>
      1 #!/usr/bin/env python
      2 
----> 3 from pandas_ml.core import ModelFrame, ModelSeries       # noqa
      4 from pandas_ml.tools import info                         # noqa
      5 from pandas_ml.version import version as __version__     # noqa

C:\g\test\lib\pandas_ml\core\__init__.py in <module>
      1 #!/usr/bin/env python
      2 
----> 3 from pandas_ml.core.frame import ModelFrame       # noqa
      4 from pandas_ml.core.series import ModelSeries     # noqa

C:\g\test\lib\pandas_ml\core\frame.py in <module>
      8 
      9 import pandas_ml.imbaccessors as imbaccessors
---> 10 import pandas_ml.skaccessors as skaccessors
     11 import pandas_ml.smaccessors as smaccessors
     12 import pandas_ml.snsaccessors as snsaccessors

C:\g\test\lib\pandas_ml\skaccessors\__init__.py in <module>
     17 from pandas_ml.skaccessors.neighbors import NeighborsMethods                      # noqa
     18 from pandas_ml.skaccessors.pipeline import PipelineMethods                        # noqa
---> 19 from pandas_ml.skaccessors.preprocessing import PreprocessingMethods              # noqa
     20 from pandas_ml.skaccessors.svm import SVMMethods                                  # noqa

C:\g\test\lib\pandas_ml\skaccessors\preprocessing.py in <module>
     11     _keep_col_classes = [pp.Binarizer,
     12                          pp.FunctionTransformer,
---> 13                          pp.Imputer,
     14                          pp.KernelCenterer,
     15                          pp.LabelEncoder,

AttributeError: module 'sklearn.preprocessing' has no attribute 'Imputer'
    opened by apiszcz 11
Releases(v0.6.1)
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