In-depth understanding of pandas in Python (code example)

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First, screening

First, create a 6X4 matrix data.

Dates = Pd.date_range (' 20180830 ', periods=6) df = PD. DataFrame (Np.arange) reshape ((6,4)), index=dates, columns=[' A ', ' B ', ' C ', ' D ']) print (DF)

Print:

             A   B   C   d2018-08-30   0   1   2   32018-08-31   4   5   6   72018-09-01   8   9  112018-09-02  152018-09-03  192018-09-04  23

Simple filtering

If we want to select DataFrame the data, the following describes two ways that they can achieve the same goal:

Print (df[' A ']) print (DF. A) "" "2018-08-30     02018-08-31     42018-09-01     82018-09-02    122018-09-03    162018-09-04    20freq:d, Name:a, Dtype:int64 "" "

Let the selection span multiple rows or columns:

Print (Df[0:3]) "" "            A  B   C   d2018-08-30  0  1   2   32018-08-31  4  5   6   72018-09-01  8 9 "" "  print (df[' 20180830 ': ' 20180901 '])" ""            A  B   C   d2018-08-30  0  1   2   32018-08-31  4  5   6   72018-09-01  8  9  10 11 "" "  

If df[3:3] it will be an empty object. The latter selects the 20180830 20180901 data between the labels and includes both tags .

You can also go through loc , iloc and ix make your choice.