After using pandas to read the relevant excel, columns, how to clean it if null values in the table
after access to the relevant information online, has been way
pandas.dropna(axis=1,how=‘any’)
axis = 0 refers to the line, if not write parameter, the default is the axis = 0,
Axis refers to the column. 1 =
how = 'any' refers to long column containing a null value, deletes the column
how = 'all' is the only representative of a null value as a whole, the column was deleted
Note that the version in python3.7
to receive the return value pandas.dropna need to have a variable
or when running the program without error but the data change will not happen
Some write about the pandas library operations excel spreadsheet
#encoding=gb18030
import numpy
import pandas as pd
data_filename = "data/data21695/数据.xlsx"
df = pd.read_excel(data_filename)
x = df.dropna(axis=1,how='any')
g=df["编号"]
y = len(g)
i=0
print(y)
del x["无机盐"]
x["无敌"]=x["身高"]
for i in range(y):
x.iloc[i,0]=i
x.to_excel('new.xlsx')
pandas.read_excel read excel spreadsheet
del [ 'inorganic salts'] delete a column called inorganic salt
X [ 'unrivaled'] = x [ 'height'] add an unrivaled named, copy the data to the height of the column of this row unrivaled
x.iloc [i, 0] obtaining the i-th row, the data in column 0
x.to_excel introduced into the excel spreadsheet named new.xlsx
