[Python--pandas] pandas reads and writes csv files---overview

Use pandas to read, save and simple operations of csv files

1. The original file format is as follows

import pandas as pd

2. File reading

data = pd.read_csv('学生月考成绩表.csv',header = None) #header注明data是否包含有标题行
data

data = pd.read_csv('学生月考成绩表.csv') #header注明data是否包含有标题行
data

3. Read and change the data in the table

1) The reading of data takes loc as an example

data.loc[0] #选取第0行元素

data.loc[0,'Math'] #选取第0行/第Math列元素

1) loc, based on the column label, can select a specific row (according to the row index);
2) iloc, based on the row/column position;
3) at, quickly locate the elements of the DataFrame according to the specified row index and column label;
4) iat , Similar to at, the difference is based on position;
5) ix, a mixture of loc and iloc, supports both label and position. Reference from [1]

2) Modification of specific values

data.shape #获取数据DataFreme格式的大小

data.iat[0,6] = 100 #将数据的第0行第6列修改为100
data

data.rename(columns={
    
    'Nmae':'Name'},inplace=True) #修改列名称
data

4. Insert and delete rows and columns

1) Add in the last line

newrow = pd.DataFrame({
    
    'Name':'lisi','Chinese':30,'Math':40,'English':50,'Science':60,'Score':70,'Ranking':6},index=[0]) #设置行标index=[0]
data = data.append(newrow,ignore_index=True)#忽略行标设置
data

2) Modify the line at the specified location

data.loc[2] = ['wangwu',30,40,50,60,70,6] #修改第2行的值

3) Add a column at the specified position

data.insert(1,'Art',[80,81,82,83,85])    #插入一列
data

3) Delete rows or columns

data.drop('Math', axis=1, inplace=True) #删除Math列，axis为1表示删除列，0表示删除行。inplace为True表示直接对原表修改。
data.drop(0, axis=0, inplace=True)#删除第0行，axis为1表示删除列，0表示删除行。inplace为True表示直接对原表修改。
data

5. The index of the element position in the table

index = data[data.Ranking == 3].index.tolist()
index

6. Save the file

data.to_csv('student_score.csv',index=False) #index = False取消行名称，header = None则取消列名称

reference

【1】https://blog.csdn.net/grllery/article/details/81292085
【2】https://blog.csdn.net/huang_susan/article/details/80626698
【3】https://blog.csdn.net/u010801439/article/details/80033341