Python編程：pandas入門，pythonpandas入門

Python編程：pandas入門，pythonpandas入門

總算找到時間學習了下pandas，先學習一部分，後面繼續補充

import pandas as pdimport numpy as npimport matplotlib.pyplot as plt# 建立序列, 讓pandas建立預設整數索引s = pd.Series([1, 3, 5, np.nan, 6, 8])print(s)"""0    1.01    3.02    5.03    NaN4    6.05    8.0dtype: float64"""# 資料讀取# csv檔案讀取# 預設第一行列名，資料從第二行起# (資料從第一行起header=None)data = pd.read_csv("data.csv")print(data)"""   id name  age  score0   1  tom   12     981   2  tom   12     982   3  tom   12     983   4  tom   12     984   5  tom   12     985   6  tom   12     986   7  tom   12     987   8  tom   12     988   9  tom   12     989  10  tom   12     98"""# 顯示前面幾行資料（預設前5行）print(data.head())"""   id name  age  score0   1  tom   12     981   2  tom   12     982   3  tom   12     983   4  tom   12     984   5  tom   12     98"""# 讀取尾部資料print(data.tail())""" id name  age  score5   6  tom   12     986   7  tom   12     987   8  tom   12     988   9  tom   12     989  10  tom   12     98"""# 顯示列名print(data.columns)# Index(['id', 'name', 'age', 'score'], dtype='object')# 顯示行號print(data.index)# RangeIndex(start=0, stop=10, step=1)# 顯示大小print(data.shape)# (10, 4)# 索引和計算# 列名預設為字串(Object)。行的index預設為整數# 提取行print(data.loc[3:6])"""   id name  age  score3   4  tom   12     984   5  tom   12     985   6  tom   12     986   7  tom   12     98"""# 使用list提取行print(data[3:6])"""   id name  age  score3   4  tom   12     984   5  tom   12     985   6  tom   12     98"""# 提取列columns = ["name", "age"]print(data[columns])"""   name  age0  tom   121  tom   122  tom   123  tom   124  tom   125  tom   126  tom   127  tom   128  tom   129  tom   12"""# 列名轉為listprint(data.columns.tolist())# ['id', 'name', 'age', 'score']print(data.columns.values)# ['id' 'name' 'age' 'score']print(data.columns.values.dtype)# object# 切片print(data.loc[3:6][["name", "age"]])"""  name  age3  tom   124  tom   125  tom   126  tom   12"""print(data["name"])"""0    tom1    tom2    tom3    tom4    tom5    tom6    tom7    tom8    tom9    tomName: name, dtype: object"""# 取極值print(data["id"].max())# 10# 運算num = data.shape[0]age_average = data["id"]/numprint(age_average.head())"""0    0.11    0.22    0.33    0.44    0.5Name: id, dtype: float64"""# 排序data.sort_values("id", inplace=False, ascending=False)print(data.head())

查看評論