Sorting Python data frame according to dates

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How to sort a python data frame according to dates in the format that can be seen on the image. The output that I want to receive is the same data frame but at index 0 I would have January 2013 and the corresponding amount and at index 1 I would have February 2013 etc.

enter image description here

edited Nov 11 at 20:52

Adam Chubbuck

810217

asked Nov 11 at 20:50

Ewa Szyszka

1

Please include an example of the code that you used to construct the dataframe shown in the image.
– Adam Chubbuck
Nov 11 at 20:54

add a comment |

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0
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favorite

enter image description here

edited Nov 11 at 20:52

Adam Chubbuck

810217

asked Nov 11 at 20:50

Ewa Szyszka

1

Please include an example of the code that you used to construct the dataframe shown in the image.
– Adam Chubbuck
Nov 11 at 20:54

add a comment |

up vote
0
down vote

favorite

enter image description here

edited Nov 11 at 20:52

Adam Chubbuck

810217

asked Nov 11 at 20:50

Ewa Szyszka

enter image description here

python pandas dataframe

edited Nov 11 at 20:52

Adam Chubbuck

810217

asked Nov 11 at 20:50

Ewa Szyszka

edited Nov 11 at 20:52

Adam Chubbuck

810217

asked Nov 11 at 20:50

Ewa Szyszka

edited Nov 11 at 20:52

Adam Chubbuck

810217

edited Nov 11 at 20:52

Adam Chubbuck

810217

edited Nov 11 at 20:52

Adam Chubbuck

810217

asked Nov 11 at 20:50

Ewa Szyszka

asked Nov 11 at 20:50

Ewa Szyszka

asked Nov 11 at 20:50

Ewa Szyszka

1

Please include an example of the code that you used to construct the dataframe shown in the image.
– Adam Chubbuck
Nov 11 at 20:54

add a comment |

1

Please include an example of the code that you used to construct the dataframe shown in the image.
– Adam Chubbuck
Nov 11 at 20:54

Please include an example of the code that you used to construct the dataframe shown in the image.
– Adam Chubbuck
Nov 11 at 20:54

add a comment |

2 Answers
2

active

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votes

up vote
1
down vote

import pandas as pd

df = pd.DataFrame( {'Amount':['54241.25','54008.83','54008.82'] ,

    'Date':['05/01/2015','05/01/2017','06/01/2017']})

df['Date'] =pd.to_datetime(df.Date)

df.sort_values('Date', inplace=True)

edited Nov 11 at 21:05

answered Nov 11 at 20:57

Keerthana Gopalakrishnan

47769

Might as well use: df.sort_values('Date', inplace=True) here...
– Jon Clements♦
Nov 11 at 21:04

updated the code :)
– Keerthana Gopalakrishnan
Nov 11 at 21:06

add a comment |

up vote
1
down vote

You just need to convert your Date column to a datetime, then you can sort the dataframe by that column

import pandas as pd



df = pd.DataFrame({'Date': ['05-2016', '05-2017', '06-2017', '01-2017', '02-2017'],

                   'Amount': [2,5,6,3,2]})



df['Date'] = pd.to_datetime(df['Date'], format='%m-%Y')

df = df.sort_values('Date').reset_index(drop=True)

Which gives:

        Date  Amount

0 2016-05-01       2

1 2017-01-01       3

2 2017-02-01       2

3 2017-05-01       5

4 2017-06-01       6

edited Nov 11 at 21:07

answered Nov 11 at 20:57

Simon

4,19393071

add a comment |

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2 Answers
2

active

oldest

votes

2 Answers
2

active

oldest

votes

up vote
1
down vote

import pandas as pd

df = pd.DataFrame( {'Amount':['54241.25','54008.83','54008.82'] ,

    'Date':['05/01/2015','05/01/2017','06/01/2017']})

df['Date'] =pd.to_datetime(df.Date)

df.sort_values('Date', inplace=True)

edited Nov 11 at 21:05

answered Nov 11 at 20:57

Keerthana Gopalakrishnan

47769

Might as well use: df.sort_values('Date', inplace=True) here...
– Jon Clements♦
Nov 11 at 21:04

updated the code :)
– Keerthana Gopalakrishnan
Nov 11 at 21:06

add a comment |

up vote
1
down vote

import pandas as pd

df = pd.DataFrame( {'Amount':['54241.25','54008.83','54008.82'] ,

    'Date':['05/01/2015','05/01/2017','06/01/2017']})

df['Date'] =pd.to_datetime(df.Date)

df.sort_values('Date', inplace=True)

edited Nov 11 at 21:05

answered Nov 11 at 20:57

Keerthana Gopalakrishnan

47769

Might as well use: df.sort_values('Date', inplace=True) here...
– Jon Clements♦
Nov 11 at 21:04

updated the code :)
– Keerthana Gopalakrishnan
Nov 11 at 21:06

add a comment |

up vote
1
down vote

import pandas as pd

df = pd.DataFrame( {'Amount':['54241.25','54008.83','54008.82'] ,

    'Date':['05/01/2015','05/01/2017','06/01/2017']})

df['Date'] =pd.to_datetime(df.Date)

df.sort_values('Date', inplace=True)

edited Nov 11 at 21:05

answered Nov 11 at 20:57

Keerthana Gopalakrishnan

47769

import pandas as pd

df = pd.DataFrame( {'Amount':['54241.25','54008.83','54008.82'] ,

    'Date':['05/01/2015','05/01/2017','06/01/2017']})

df['Date'] =pd.to_datetime(df.Date)

df.sort_values('Date', inplace=True)

edited Nov 11 at 21:05

answered Nov 11 at 20:57

Keerthana Gopalakrishnan

47769

edited Nov 11 at 21:05

answered Nov 11 at 20:57

Keerthana Gopalakrishnan

47769

answered Nov 11 at 20:57

Keerthana Gopalakrishnan

47769

answered Nov 11 at 20:57

Keerthana Gopalakrishnan

47769

Might as well use: df.sort_values('Date', inplace=True) here...
– Jon Clements♦
Nov 11 at 21:04

updated the code :)
– Keerthana Gopalakrishnan
Nov 11 at 21:06

add a comment |

Might as well use: df.sort_values('Date', inplace=True) here...
– Jon Clements♦
Nov 11 at 21:04

updated the code :)
– Keerthana Gopalakrishnan
Nov 11 at 21:06

Might as well use: df.sort_values('Date', inplace=True) here...
– Jon Clements♦
Nov 11 at 21:04

updated the code :)
– Keerthana Gopalakrishnan
Nov 11 at 21:06

add a comment |

up vote
1
down vote

You just need to convert your Date column to a datetime, then you can sort the dataframe by that column

import pandas as pd



df = pd.DataFrame({'Date': ['05-2016', '05-2017', '06-2017', '01-2017', '02-2017'],

                   'Amount': [2,5,6,3,2]})



df['Date'] = pd.to_datetime(df['Date'], format='%m-%Y')

df = df.sort_values('Date').reset_index(drop=True)

Which gives:

        Date  Amount

0 2016-05-01       2

1 2017-01-01       3

2 2017-02-01       2

3 2017-05-01       5

4 2017-06-01       6

edited Nov 11 at 21:07

answered Nov 11 at 20:57

Simon

4,19393071

add a comment |

up vote
1
down vote

You just need to convert your Date column to a datetime, then you can sort the dataframe by that column

import pandas as pd



df = pd.DataFrame({'Date': ['05-2016', '05-2017', '06-2017', '01-2017', '02-2017'],

                   'Amount': [2,5,6,3,2]})



df['Date'] = pd.to_datetime(df['Date'], format='%m-%Y')

df = df.sort_values('Date').reset_index(drop=True)

Which gives:

        Date  Amount

0 2016-05-01       2

1 2017-01-01       3

2 2017-02-01       2

3 2017-05-01       5

4 2017-06-01       6

edited Nov 11 at 21:07

answered Nov 11 at 20:57

Simon

4,19393071

add a comment |

up vote
1
down vote

You just need to convert your Date column to a datetime, then you can sort the dataframe by that column

import pandas as pd



df = pd.DataFrame({'Date': ['05-2016', '05-2017', '06-2017', '01-2017', '02-2017'],

                   'Amount': [2,5,6,3,2]})



df['Date'] = pd.to_datetime(df['Date'], format='%m-%Y')

df = df.sort_values('Date').reset_index(drop=True)

Which gives:

        Date  Amount

0 2016-05-01       2

1 2017-01-01       3

2 2017-02-01       2

3 2017-05-01       5

4 2017-06-01       6

edited Nov 11 at 21:07

answered Nov 11 at 20:57

Simon

4,19393071

You just need to convert your Date column to a datetime, then you can sort the dataframe by that column

import pandas as pd



df = pd.DataFrame({'Date': ['05-2016', '05-2017', '06-2017', '01-2017', '02-2017'],

                   'Amount': [2,5,6,3,2]})



df['Date'] = pd.to_datetime(df['Date'], format='%m-%Y')

df = df.sort_values('Date').reset_index(drop=True)

Which gives:

        Date  Amount

0 2016-05-01       2

1 2017-01-01       3

2 2017-02-01       2

3 2017-05-01       5

4 2017-06-01       6

edited Nov 11 at 21:07

answered Nov 11 at 20:57

Simon

4,19393071

edited Nov 11 at 21:07

answered Nov 11 at 20:57

Simon

4,19393071

answered Nov 11 at 20:57

Simon

4,19393071

answered Nov 11 at 20:57

Simon

4,19393071

add a comment |

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