目录
实战场景:Pandas如何获取表格的信息和基本数据统计
文件读写
基础语法
Pandas
Pandas的Series对象
numpy
马上安排!
- import pandas as pd
- import numpy as np
-
- df = pd.DataFrame( data={ "norm": np.random.normal(loc=0, scale=1, size=1000), "uniform": np.random.uniform(low=0, high=1, size=1000), "binomial": np.random.binomial(n=1, p=0.2, size=1000)}, index=pd.date_range(start='2021-01-01', periods=1000))
-
- # df.info(),查看多少行,多少列,类型等基本信息
- # df.describe(),查看每列的平均值、最小值、最大值、中位数等统计信息;
- print(df.info())
- print()
- print(df.describe())
DatetimeIndex: 1000 entries, 2021-01-01 to 2023-09-27
Freq: D
Data columns (total 3 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 norm 1000 non-null float64
1 uniform 1000 non-null float64
2 binomial 1000 non-null int32
dtypes: float64(2), int32(1)
memory usage: 27.3 KB
None
norm uniform binomial
count 1000.000000 1000.000000 1000.000000
mean -0.028664 0.496156 0.215000
std 0.987493 0.292747 0.411028
min -3.110249 0.000629 0.000000
25% -0.697858 0.238848 0.000000
50% -0.023654 0.503438 0.000000
75% 0.652157 0.746672 0.000000
max 3.333271 0.997617 1.000000
菜鸟实战,坚持学习!