Basic Data Inspection#
Display Top Rows (df.head())#
This command,df.head(), displays the first five rows of the DataFrame, providing a quick glimpse of the data, including column names and some of the values.
A B C D E
0 81 0.692744 Yes 2023-01-01 -1.082325
1 54 0.316586 Yes 2023-01-02 0.031455
2 57 0.860911 Yes 2023-01-03 -2.599667
3 6 0.182256 No 2023-01-04 -0.603517
4 82 0.210502 No 2023-01-05 -0.484947
Display Bottom Rows (df.tail())#
This command,df.tail(), shows the last five rows of the DataFrame, useful for checking the end of your dataset.
A B C D E
5 73 0.463415 No 2023-01-06 -0.442890
6 13 0.513276 No 2023-01-07 -0.289926
7 23 0.528147 Yes 2023-01-08 1.521620
8 87 0.138674 Yes 2023-01-09 -0.026802
9 39 0.005347 No 2023-01-10 -0.159331
Display Data Types (df.dtypes)#
This command, df.types(), returns the data types of each column in the DataFrame. It's helpful to understand the kind of data (integers, floats, strings, etc.) each column holds.
A int64
B float64
C object
D datetime64[ns]
E float64
Summary Statistics (df.describe())#
This command, df.describe(), provides descriptive statistics that summarize the central tendency, dispersion, and shape of a dataset’s distribution, excluding NaN values. It's useful for a quick statistical overview.
A B E
count 10.000000 10.000000 10.000000
mean 51.500000 0.391186 -0.413633
std 29.963867 0.267698 1.024197
min 6.000000 0.005347 -2.599667
25% 27.000000 0.189317 -0.573874
50% 55.500000 0.390001 -0.366408
75% 79.000000 0.524429 -0.059934
max 87.000000 0.860911 1.521620
Display Index, Columns, and Data (df.info())#
This command, df.info(), provides a concise summary of the DataFrame, including the number of non-null values in each column and the memory usage. It's essential for initial data assessment.
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 10 entries, 0 to 9
Data columns (total 5 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 A 10 non-null int64
1 B 10 non-null float64
2 C 10 non-null object
3 D 10 non-null datetime64[ns]
4 E 10 non-null float64
dtypes: datetime64[ns](1), float64(2), int64(1), object(1)
memory usage: 528.0 bytes