pandas with Excel Data

1. pandas operation Excel spreadsheet

　　There is an Excel file contains a two-page sheet

　　

　　Read Excel files in two ways:　

# Method, the default read first form 
Import PANDAS AS pd
DF = pd.read_excel ( " filename " ) # default open first Excel spreadsheet 
Data = df.head () # Default Read first five 
Print ( " Get all the values: \ n-{0} " .format ( Data)) # format output

demo

# Method Two: to read the name of the form specified by way 
Import PANDAS time pd
DF = pd.read_excel ( ' lemon.xlsx ' , sheet_name = ' Student ' ) # can be specified by the read sheet_name Form 
Data = df.head () # data before the default read line 5 
Print ( " Get all values: \ n-{0} " .format (Data)) # format output

Method Two

# Method three: a form specified by the index to access a form, a form represents 0 
# dual form name and the mode index can be used to locate the form 
# may also be positioned at the same time form a plurality, are listed as follows embodiment 
df = pd.read_excel ( ' lemon.xlsx ' , SHEET_NAME = [ ' Python ' , ' Student ' ]) # can be specified by name at the same time form a plurality of 
# DF = pd.read_excel ( 'lemon.xlsx', SHEET_NAME = 0) may # form specified by the read index sheet 
# DF = pd.read_excel ( 'lemon.xlsx', SHEET_NAME = [ 'Python',. 1]) may be mixed # way to specify 
# DF = pd.read_excel ( 'lemon.xlsx ', sheet_name = [1,2]) # index can be specified by a plurality of simultaneous 
data = df.values # acquired all the data, can not pay attention to this head () method oh ~ 
Print ( " Get all the values are:\n{0}" .Format (Data)) # format output

Method Three

2. pandas operations the ranks of Excel

1 Read specified single row, there will be data list
 Import PANDAS AS PD
DF = pd.read_excel ( ' lemon.xlsx ' ) # This default read directly into the first form Excel 
Data df.ix = [0] .values # 0 is the first row and read the data does not contain header, to pay attention to Oh! 
Print ( " read data specified line: \ n-{0} " .format (Data))

2 Read multiple lines specified
df=pd.read_excel('lemon.xlsx')
Data . df.ix = [[1,2]] values # reads the specified multiple rows, it is necessary IX [] a list of specified number of lines nested inside 
Print ( " read data specified row: \ n {0} " .format (the Data))

3 Read the ranks specified
df=pd.read_excel('lemon.xlsx')
data = df.ix [[1,2], [ ' title ' , ' data ' ]]. values # reads the value in the title column of the first row and the second data line, where the need nested list 
Print ( " Read data taking the specified row: \ n-{0} " .format (data))

4 Read multiple columns and rows specified value
df=pd.read_excel('lemon.xlsx')
data = df.ix [[1,2], [ ' title ' , ' data ' ]]. values # reads the value in the title column of the first row and the second data line, where the need nested list 
Print ( " Read data taking the specified row: \ n-{0} " .format (data))

5 Get all the rows of the specified column
df=pd.read_excel('lemon.xlsx')
data = df.ix [:, [ ' title ' , ' data ' ]] values. # read title data and the value of the column for all rows, where the need nested list 
Print ( " read data specified line: \ n { } 0 " .format (Data))

6 . Gets the line number and print out
DF = pd.read_excel ( ' lemon.xlsx ' )
 Print ( " List Output line numbers " , df.index.values)

7 . Gets the column name and print output
DF = pd.read_excel ( ' lemon.xlsx ' )
 Print ( " output column heading " , df.columns.values)

8 . Gets the value of a specified number of rows:
DF = pd.read_excel ( ' lemon.xlsx ' )
 Print ( " output value " , df.sample (. 3) .values) # This method is similar head () method, and a method df.values

9 . Gets the value of the specified column
DF = pd.read_excel ( ' lemon.xlsx ' )
 Print ( " output value \ n- " , DF [ ' Data ' ] .values)

Read ranks

3. pandas become Excel Data Dictionary

workbook = pd.read_excel(self.excelpath, sheet_name=self.sheet)
            test_data = []
            for i in workbook.index.values:
                if self.sheet == 0:
                    row_data = workbook.ix[i, ["case_id", "title", "data"]].to_dict()
                elif self.sheet == 1:
                    row_data = workbook.ix[i, ["name", "age", "ks", "ksh", "money", "phone"]].to_dict()
                else:
                    row_data = workbook.ix[
                        i, ["case_id", "case_name", "case_data", "case_header", "case_method", "case_url", "case_port",
                            "case_yq_reault"
                            ]]
                test_data.append(row_data)

pandas will be processed into Excel Dictionary