pandas gets the number of rows, columns, and elements of the dataframe

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1. Test data

1457822940      0       0       44      36
422692440       0       0       3       3
1460826600      0       0       7       6
1410115140      -1      3       25      7
1161370800      0       0       18      14
996746700       0       0       30      25
1115896320      0       0       441     123
64954980        0       0       7       7
2307334696      0       0       2       2
417770700       0       0       1       1

2. Get the number of rows, columns, elements, etc.

def test():
        names = ['c1', 'c2', 'c3', 'c4', 'c5']
        df = pd.read_csv("testdata", sep="\t", header=None, names=names)
        print(df.info())
        print("\n")
        print("len is: ", len(df))
        print("columns is: ", df.columns)
        print("shape is: ", df.shape)
        print("size is: ", df.size)

Code output result:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 10 entries, 0 to 9
Data columns (total 5 columns):
 #   Column  Non-Null Count  Dtype
---  ------  --------------  -----
 0   c1      10 non-null     int64
 1   c2      10 non-null     int64
 2   c3      10 non-null     int64
 3   c4      10 non-null     int64
 4   c5      10 non-null     int64
dtypes: int64(5)
memory usage: 528.0 bytes
None


len is:  10
columns is:  Index(['c1', 'c2', 'c3', 'c4', 'c5'], dtype='object')
shape is:  (10, 5)
size is:  50

Among them, the info() method contains a lot of information, including type, column information, number of non-null, data type, memory usage, etc.

len(df) can get the number of rows of the dataframe
column can get the information related to the column
shape is a two-tuple, including row and column information, so if you want to get the row and column data of the dataframe, you can get it through shape.
size is the number of elements in the entire dataframe.

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Origin blog.csdn.net/bitcarmanlee/article/details/112376886