REGISTRO_DATAFRAME

microbill.objects.REGISTRO_DATAFRAME = Cotización Fecha Nombre ... Aplicó Tipo de Pago Valor 0 U0619-0044 2019-11-03 12:50:25 Juan Barbosa ... Transferencia interna 194,300 1 U0619-0043 2019-11-02 17:14:24 Juan Barbosa ... Transferencia interna 194,300 2 C19-0016 2019-03-20 14:49:14 Paola Ruiz Puentes ... Transferencia interna 624,000 3 C19-0015 2019-03-19 16:36:24 Diana Marcela Castilla ... Factura 1,900,000 4 C19-0014 2019-03-12 18:46:03 Adriana Bernal ... Transferencia interna 1,164,800 5 C19-0013 2019-02-22 16:07:04 Laura Lorena Cardenas ... Transferencia interna 312,000 6 C19-0012 2019-02-20 14:01:15 Paula Andrea Guerrero ... Transferencia interna 208,000 7 C19-0011 2019-02-20 11:42:49 Angela Johana Espejo Mojica ... Factura 416,000 8 C19-0010 2019-02-21 13:28:06 Ruth Dayana Hernandez Reyes ... Transferencia interna 2,392,000 9 C19-0009 2019-02-19 12:26:49 Diana Marcela Gutierrez Saldaña ... Factura 3,000,000 10 C19-0008 2019-03-20 11:03:43 Andrés Baquero ... Factura 1,720,000 11 C19-0007 2019-02-06 14:35:06 Juliana Carolina Montoya Bohórquez ... Transferencia interna 104,000 12 C19-0006 2019-02-05 10:56:16 Andreas Reiber ... Transferencia interna 97,500 13 C19-0005 2019-02-04 09:51:04 Amalia Murgueitio Calle ... Transferencia interna 650,000 14 C19-0004 2019-02-01 15:56:56 Nicolas Estrada Mejia ... Transferencia interna 208,000 15 C19-0003 2019-03-04 09:21:30 Paula Andrea Guerrero ... Transferencia interna 1,768,000 16 C19-0002 2019-01-22 16:39:56 Juan Carlos Cruz Jimenez ... Transferencia interna 1,248,000 17 C19-0001 2019-01-21 16:01:50 Sara Paredes Echeverri ... Transferencia interna 195,000 18 C18-0057 2018-11-28 14:35:15 Dory Lineth Gomez ... Recibo 688,000 19 C18-0056 2018-11-23 10:27:37 Esteban Cespedes Diaz ... Transferencia interna 65,000 20 C18-0055 2018-11-01 15:32:59 Juan Barbosa ... Transferencia interna 65,000 21 C18-0054 2018-10-25 14:00:43 Juan Carlos Cruz Jimenez ... Transferencia interna 832,000 22 C18-0053 2018-10-11 16:18:22 Andrea Tobian Herreño ... Transferencia interna 104,000 23 C18-0052 2018-09-28 17:14:07 Laura Lorena Cardenas ... Transferencia interna 104,000 24 C18-0051 2018-10-08 12:11:20 Laura Lorena Cardenas ... Transferencia interna 1,040,000 25 C18-0050 2018-10-03 13:22:17 Alba Avila ... Laura Sotelo Transferencia interna 208,000 26 C18-0049 2018-09-17 17:10:32 Alba Avila ... Transferencia interna 208,000 27 C18-0048 2018-09-17 15:25:21 Andreas Reiber ... Transferencia interna 104,000 28 C18-0047 2018-09-10 16:41:04 Christian Camilo Falla Pinilla ... Transferencia interna 832,000 29 C18-0046 2018-09-10 14:08:44 Christian Camilo Falla Pinilla ... Transferencia interna 1,040,000 .. ... ... ... ... ... ... ... 766 0219-0024 2019-04-29 12:00:24 Viviana Lizeth Olaya Pinzón ... Recibo 95,000 767 0219-0023 2019-04-29 10:31:05 Vicente Benavides ... Factura 104,000 768 0219-0022 2019-04-25 15:15:39 Mauricio Galeano ... Transferencia interna 45,000 769 0219-0021 2019-04-24 14:41:32 Andres Ricardo Velasco Gonzalez ... Transferencia interna 45,000 770 0219-0020 2019-04-22 16:43:59 Juan Sebastian Woodcock ... Transferencia interna 45,000 771 0219-0019 2019-04-22 16:39:01 Angelica Chica Segovia ... Factura 475,000 772 0219-0018 2019-04-22 16:00:12 Omar Steven Castaño ... Recibo 208,000 773 0219-0017 2019-04-22 15:04:01 Andrés Baquero ... Transferencia interna 380,000 774 0219-0016 2019-04-22 08:28:29 Johana Andrea Barrera Gonzalez ... Transferencia interna 45,000 775 0219-0015 2019-04-12 15:44:45 Mariana Gutierrez ... Transferencia interna 45,000 776 0219-0014 2019-04-12 10:28:05 Francisco Ibla ... Recibo 95,000 777 0219-0013 2019-04-11 14:46:10 Pablo Emilio Realpe ... Transferencia interna 45,000 778 0219-0012 2019-04-11 14:29:48 Pablo Emilio Realpe ... Transferencia interna 90,000 779 0219-0011 2019-04-09 15:13:06 Carlos Rafael Castillo Saldarriaga ... Factura 415,000 780 0219-0010 2019-04-04 09:06:09 Amalia Murgueitio Calle ... Transferencia interna 270,000 781 0219-0009 2019-04-03 11:47:26 diego andres barrero rosero ... Transferencia interna 90,000 782 0219-0008 2019-04-01 17:01:16 Paula Andrea Guerrero Barragán ... Transferencia interna 103,000 783 0219-0007 2019-04-01 11:11:54 Alejandro Arellano Ayala ... Transferencia interna 600,000 784 0219-0006 2019-03-29 14:57:12 Lizeth Xiomara Vargas Rincon ... Transferencia interna 195,000 785 0219-0005 2019-03-28 16:14:41 Lizeth Xiomara Vargas Rincon ... Transferencia interna 39,000 786 0219-0004 2019-03-26 10:09:12 Francisco Ibla ... Recibo 64,000 787 0219-0003 2019-03-22 15:52:08 Mario Omar Fernández ... Recibo 64,000 788 0219-0002 2019-03-22 15:34:36 Mario Omar Fernández ... Transferencia interna 39,000 789 0219-0001 2019-03-22 09:48:29 Marylin Hidalgo ... Factura 222,000 790 0119-0006 2019-09-08 19:25:03 Juan Barbosa ... Transferencia interna 20,000 791 0119-0005 2019-09-08 19:24:45 Juan Barbosa ... Transferencia interna 20,000 792 0119-0004 2019-09-08 19:24:27 Juan Barbosa ... Transferencia interna 20,000 793 0119-0003 2019-09-08 19:20:30 Juan Barbosa ... Transferencia interna 20,000 794 0119-0002 2019-09-08 19:14:56 Juan Barbosa ... Transferencia interna 20,000 795 0119-0001 2019-09-08 19:13:02 Juan Barbosa ... Transferencia interna 20,000 [796 rows x 18 columns]

Two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. Can be thought of as a dict-like container for Series objects. The primary pandas data structure.

Parameters

datanumpy ndarray (structured or homogeneous), dict, or DataFrame

Dict can contain Series, arrays, constants, or list-like objects

Distinto en la versión 0.23.0: If data is a dict, argument order is maintained for Python 3.6 and later.

indexIndex or array-like

Index to use for resulting frame. Will default to RangeIndex if no indexing information part of input data and no index provided

columnsIndex or array-like

Column labels to use for resulting frame. Will default to RangeIndex (0, 1, 2, …, n) if no column labels are provided

dtypedtype, default None

Data type to force. Only a single dtype is allowed. If None, infer

copyboolean, default False

Copy data from inputs. Only affects DataFrame / 2d ndarray input

Ver también

DataFrame.from_records

constructor from tuples, also record arrays

DataFrame.from_dict

from dicts of Series, arrays, or dicts

DataFrame.from_items

from sequence of (key, value) pairs

pandas.read_csv, pandas.read_table, pandas.read_clipboard

Examples

Constructing DataFrame from a dictionary.

>>> d = {'col1': [1, 2], 'col2': [3, 4]}
>>> df = pd.DataFrame(data=d)
>>> df
   col1  col2
0     1     3
1     2     4

Notice that the inferred dtype is int64.

>>> df.dtypes
col1    int64
col2    int64
dtype: object

To enforce a single dtype:

>>> df = pd.DataFrame(data=d, dtype=np.int8)
>>> df.dtypes
col1    int8
col2    int8
dtype: object

Constructing DataFrame from numpy ndarray:

>>> df2 = pd.DataFrame(np.random.randint(low=0, high=10, size=(5, 5)),
...                    columns=['a', 'b', 'c', 'd', 'e'])
>>> df2
    a   b   c   d   e
0   2   8   8   3   4
1   4   2   9   0   9
2   1   0   7   8   0
3   5   1   7   1   3
4   6   0   2   4   2