Comparing OrderDict of DataFrames

I am facing a comparing problem, this is my code:

import pandas as pd

from collections import OrderedDict

from pandas.util.testing import assert_frame_equal



df1 = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),

     'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd']),

    'three' : pd.Series([1., 2., 3., 4., 5.], index=['a', 'b', 'c', 'd','e'])}



df2 = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),

     'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd']),

    'three' : pd.Series([1., 2., 3., 4., 5.], index=['a', 'b', 'c', 'd','e'])}

od = OrderedDict() 

od['a'] = pd.DataFrame(df1)

od['b'] = pd.DataFrame(df1)

od['c'] = pd.DataFrame(df1)

od['d'] = pd.DataFrame(df1)



od2 = OrderedDict() 

od2['a'] = pd.DataFrame(df2)

od2['b'] = pd.DataFrame(df2)

od2['c'] = pd.DataFrame(df2)

od2['d'] = pd.DataFrame(df2)



test = assert_frame_equal(od, od2)

print(test)

I have 2 OrderedDict made of pandas DataFrames and I would like to analyze if the single elements inside the DataFrames are equal.

I found the function assert_frame_equal that works perfectly when it comes to compare 2 DataFrames, but gives this error with OrderedDict:

AssertionError: DataFrame Expected type class
'pandas.core.frame.DataFrame', found class
'collections.OrderedDict' instead

Is there any solution or workaround to this? Take into account that I necessarily start from an OrderedDict and unfortunately I cannot change that.

Thanks so much in advance any help/hint on this issue.

asked Nov 15 '18 at 16:22

iraciv94

14810

add a comment |

I am facing a comparing problem, this is my code:

import pandas as pd

from collections import OrderedDict

from pandas.util.testing import assert_frame_equal



df1 = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),

     'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd']),

    'three' : pd.Series([1., 2., 3., 4., 5.], index=['a', 'b', 'c', 'd','e'])}



df2 = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),

     'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd']),

    'three' : pd.Series([1., 2., 3., 4., 5.], index=['a', 'b', 'c', 'd','e'])}

od = OrderedDict() 

od['a'] = pd.DataFrame(df1)

od['b'] = pd.DataFrame(df1)

od['c'] = pd.DataFrame(df1)

od['d'] = pd.DataFrame(df1)



od2 = OrderedDict() 

od2['a'] = pd.DataFrame(df2)

od2['b'] = pd.DataFrame(df2)

od2['c'] = pd.DataFrame(df2)

od2['d'] = pd.DataFrame(df2)



test = assert_frame_equal(od, od2)

print(test)

I have 2 OrderedDict made of pandas DataFrames and I would like to analyze if the single elements inside the DataFrames are equal.

I found the function assert_frame_equal that works perfectly when it comes to compare 2 DataFrames, but gives this error with OrderedDict:

AssertionError: DataFrame Expected type class
'pandas.core.frame.DataFrame', found class
'collections.OrderedDict' instead

Is there any solution or workaround to this? Take into account that I necessarily start from an OrderedDict and unfortunately I cannot change that.

Thanks so much in advance any help/hint on this issue.

asked Nov 15 '18 at 16:22

iraciv94

14810

add a comment |

I am facing a comparing problem, this is my code:

import pandas as pd

from collections import OrderedDict

from pandas.util.testing import assert_frame_equal



df1 = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),

     'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd']),

    'three' : pd.Series([1., 2., 3., 4., 5.], index=['a', 'b', 'c', 'd','e'])}



df2 = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),

     'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd']),

    'three' : pd.Series([1., 2., 3., 4., 5.], index=['a', 'b', 'c', 'd','e'])}

od = OrderedDict() 

od['a'] = pd.DataFrame(df1)

od['b'] = pd.DataFrame(df1)

od['c'] = pd.DataFrame(df1)

od['d'] = pd.DataFrame(df1)



od2 = OrderedDict() 

od2['a'] = pd.DataFrame(df2)

od2['b'] = pd.DataFrame(df2)

od2['c'] = pd.DataFrame(df2)

od2['d'] = pd.DataFrame(df2)



test = assert_frame_equal(od, od2)

print(test)

I have 2 OrderedDict made of pandas DataFrames and I would like to analyze if the single elements inside the DataFrames are equal.

I found the function assert_frame_equal that works perfectly when it comes to compare 2 DataFrames, but gives this error with OrderedDict:

AssertionError: DataFrame Expected type class
'pandas.core.frame.DataFrame', found class
'collections.OrderedDict' instead

Is there any solution or workaround to this? Take into account that I necessarily start from an OrderedDict and unfortunately I cannot change that.

Thanks so much in advance any help/hint on this issue.

asked Nov 15 '18 at 16:22

iraciv94

14810

I am facing a comparing problem, this is my code:

import pandas as pd

from collections import OrderedDict

from pandas.util.testing import assert_frame_equal



df1 = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),

     'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd']),

    'three' : pd.Series([1., 2., 3., 4., 5.], index=['a', 'b', 'c', 'd','e'])}



df2 = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),

     'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd']),

    'three' : pd.Series([1., 2., 3., 4., 5.], index=['a', 'b', 'c', 'd','e'])}

od = OrderedDict() 

od['a'] = pd.DataFrame(df1)

od['b'] = pd.DataFrame(df1)

od['c'] = pd.DataFrame(df1)

od['d'] = pd.DataFrame(df1)



od2 = OrderedDict() 

od2['a'] = pd.DataFrame(df2)

od2['b'] = pd.DataFrame(df2)

od2['c'] = pd.DataFrame(df2)

od2['d'] = pd.DataFrame(df2)



test = assert_frame_equal(od, od2)

print(test)

I have 2 OrderedDict made of pandas DataFrames and I would like to analyze if the single elements inside the DataFrames are equal.

I found the function assert_frame_equal that works perfectly when it comes to compare 2 DataFrames, but gives this error with OrderedDict:

AssertionError: DataFrame Expected type class
'pandas.core.frame.DataFrame', found class
'collections.OrderedDict' instead

Is there any solution or workaround to this? Take into account that I necessarily start from an OrderedDict and unfortunately I cannot change that.

Thanks so much in advance any help/hint on this issue.

python-3.x pandas dictionary dataframe compare

asked Nov 15 '18 at 16:22

iraciv94

14810

asked Nov 15 '18 at 16:22

iraciv94

14810

asked Nov 15 '18 at 16:22

iraciv94

14810

asked Nov 15 '18 at 16:22

iraciv94

14810

asked Nov 15 '18 at 16:22

iraciv94

14810

add a comment |

2 Answers
2

active

oldest

votes

Something like this?

for df1, df2 in zip(od.values(), od2.values()):

    test = assert_frame_equal(df1, df2)

    print(test)

Returns:

None

None

None

None

Also, you are calling your initial OrderedDicts df1, which might lead to some confusion later on. By convention, df is short for DataFrame.

You can also use equal, per What is the difference between `assert_frame_equal` and `equals`

for df1, df2 in zip(od.values(), od2.values()):

    test = df1.equals(df2)

    print(test)

Returns:

True

True

True

True

answered Nov 15 '18 at 18:34

Evan

1,141516

add a comment |

Look if this helps. Using zip()

for ord1, ord2 in zip(od.values(), od2.values()):



    print(assert_frame_equal(ord1, ord2))



    # or you can also use 

    print(ord1.equals(ord2))

Hope this helps

edited Nov 29 '18 at 18:16

answered Nov 15 '18 at 18:29

Srce Cde

1,186512

The values in od and od2 are dataframes, so I don't think the constructor needs to be called. k and v are shorthand for key and value, so using k to refer to od.values() may be confusing for some.

– Evan
Nov 15 '18 at 18:35

@Evan I agree with you.

– Srce Cde
Nov 15 '18 at 18:41

add a comment |

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2 Answers
2

active

oldest

votes

2 Answers
2

active

oldest

votes

Something like this?

for df1, df2 in zip(od.values(), od2.values()):

    test = assert_frame_equal(df1, df2)

    print(test)

Returns:

None

None

None

None

Also, you are calling your initial OrderedDicts df1, which might lead to some confusion later on. By convention, df is short for DataFrame.

You can also use equal, per What is the difference between `assert_frame_equal` and `equals`

for df1, df2 in zip(od.values(), od2.values()):

    test = df1.equals(df2)

    print(test)

Returns:

True

True

True

True

answered Nov 15 '18 at 18:34

Evan

1,141516

add a comment |

Something like this?

for df1, df2 in zip(od.values(), od2.values()):

    test = assert_frame_equal(df1, df2)

    print(test)

Returns:

None

None

None

None

Also, you are calling your initial OrderedDicts df1, which might lead to some confusion later on. By convention, df is short for DataFrame.

You can also use equal, per What is the difference between `assert_frame_equal` and `equals`

for df1, df2 in zip(od.values(), od2.values()):

    test = df1.equals(df2)

    print(test)

Returns:

True

True

True

True

answered Nov 15 '18 at 18:34

Evan

1,141516

add a comment |

Something like this?

for df1, df2 in zip(od.values(), od2.values()):

    test = assert_frame_equal(df1, df2)

    print(test)

Returns:

None

None

None

None

Also, you are calling your initial OrderedDicts df1, which might lead to some confusion later on. By convention, df is short for DataFrame.

You can also use equal, per What is the difference between `assert_frame_equal` and `equals`

for df1, df2 in zip(od.values(), od2.values()):

    test = df1.equals(df2)

    print(test)

Returns:

True

True

True

True

answered Nov 15 '18 at 18:34

Evan

1,141516

Something like this?

for df1, df2 in zip(od.values(), od2.values()):

    test = assert_frame_equal(df1, df2)

    print(test)

Returns:

None

None

None

None

Also, you are calling your initial OrderedDicts df1, which might lead to some confusion later on. By convention, df is short for DataFrame.

You can also use equal, per What is the difference between `assert_frame_equal` and `equals`

for df1, df2 in zip(od.values(), od2.values()):

    test = df1.equals(df2)

    print(test)

Returns:

True

True

True

True

answered Nov 15 '18 at 18:34

Evan

1,141516

answered Nov 15 '18 at 18:34

Evan

1,141516

answered Nov 15 '18 at 18:34

Evan

1,141516

answered Nov 15 '18 at 18:34

Evan

1,141516

add a comment |

Look if this helps. Using zip()

for ord1, ord2 in zip(od.values(), od2.values()):



    print(assert_frame_equal(ord1, ord2))



    # or you can also use 

    print(ord1.equals(ord2))

Hope this helps

edited Nov 29 '18 at 18:16

answered Nov 15 '18 at 18:29

Srce Cde

1,186512

The values in od and od2 are dataframes, so I don't think the constructor needs to be called. k and v are shorthand for key and value, so using k to refer to od.values() may be confusing for some.

– Evan
Nov 15 '18 at 18:35

@Evan I agree with you.

– Srce Cde
Nov 15 '18 at 18:41

add a comment |

Look if this helps. Using zip()

for ord1, ord2 in zip(od.values(), od2.values()):



    print(assert_frame_equal(ord1, ord2))



    # or you can also use 

    print(ord1.equals(ord2))

Hope this helps

edited Nov 29 '18 at 18:16

answered Nov 15 '18 at 18:29

Srce Cde

1,186512

The values in od and od2 are dataframes, so I don't think the constructor needs to be called. k and v are shorthand for key and value, so using k to refer to od.values() may be confusing for some.

– Evan
Nov 15 '18 at 18:35

@Evan I agree with you.

– Srce Cde
Nov 15 '18 at 18:41

add a comment |

Look if this helps. Using zip()

for ord1, ord2 in zip(od.values(), od2.values()):



    print(assert_frame_equal(ord1, ord2))



    # or you can also use 

    print(ord1.equals(ord2))

Hope this helps

edited Nov 29 '18 at 18:16

answered Nov 15 '18 at 18:29

Srce Cde

1,186512

Look if this helps. Using zip()

for ord1, ord2 in zip(od.values(), od2.values()):



    print(assert_frame_equal(ord1, ord2))



    # or you can also use 

    print(ord1.equals(ord2))

Hope this helps

edited Nov 29 '18 at 18:16

answered Nov 15 '18 at 18:29

Srce Cde

1,186512

edited Nov 29 '18 at 18:16

answered Nov 15 '18 at 18:29

Srce Cde

1,186512

answered Nov 15 '18 at 18:29

Srce Cde

1,186512

answered Nov 15 '18 at 18:29

Srce Cde

1,186512

The values in od and od2 are dataframes, so I don't think the constructor needs to be called. k and v are shorthand for key and value, so using k to refer to od.values() may be confusing for some.

– Evan
Nov 15 '18 at 18:35

@Evan I agree with you.

– Srce Cde
Nov 15 '18 at 18:41

add a comment |

The values in od and od2 are dataframes, so I don't think the constructor needs to be called. k and v are shorthand for key and value, so using k to refer to od.values() may be confusing for some.

– Evan
Nov 15 '18 at 18:35

@Evan I agree with you.

– Srce Cde
Nov 15 '18 at 18:41

The values in od and od2 are dataframes, so I don't think the constructor needs to be called. k and v are shorthand for key and value, so using k to refer to od.values() may be confusing for some.

– Evan
Nov 15 '18 at 18:35

@Evan I agree with you.

– Srce Cde
Nov 15 '18 at 18:41

add a comment |

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