python pandas data cleaning

', Index=false) Except Exception as E: print (E.message) Run, OK, can be stored in the index parameter indicates whether the Dataframe index as a column to store, generally not required, so the assignment is False Now it seems that the problem is solved, but there is a small problem.If I have a CSV file that contains Chinese (i window):Name Age classXiao Ming 151 gradeXiao Zhang 183 grade engine = Create_engine (str (r "mysql+mysqldb://%s:" + '%s ' + "@%s/%s")% (user, password, host, db)) Tr

Python pandas common functions, pythonpandas This article focuses on pandas common functions.1 import Statement import pandas as pdimport numpy as npimport matplotlib.pyplot as pltimport datetimeimport re2. File Reading Df = pd.read_csv(path+'file.csv ')Parameter: header = None use the default column name, 0, 1, 2, 3

lines for GD and HN, you can do this: In [8]: Df[df.p1.isin ([' GD ', ' HN '])]out[8]: p1 p2 p30 GD GX FJ2 HN HB AH But if we want data beyond these two lines, we need to get around the point. The principle is to first remove the P1 and convert it to a list, then remove the unwanted rows (values) from the list and then use them in the Dataframeisin() In [9]: Ex_list = List (DF.P1) in [ten]: Ex_list.remove (' GD ') in [all]: Ex_list.remove (' HN ') in

Summary One, create object two, view data three, select and set four, missing value processing Five, related Operations VI, aggregation seven, rearrangement (reshaping)Viii. Time Series 　　 Nine, categorical type ten, drawing Xi. Import and save data content# Coding=utf-8import pandas as PDimport NumPy as NP# # # One, create object# 1. You can pass a list object t

Data type to force. Only a single dtype is allowed. If None, infer Copy : boolean, default False Copy data from inputs. Only affects dataframe/2d Ndarray input See Also DataFrame.from_records constructor from tuples, also record arrays Dat

([arr, arr], Axis=1) # Connect two arr, in the direction of the row---------------Pandas-----------------------Ser = series () Ser = series ([...], index=[...]) #一维数组, dictionaries can be converted directly to Seriesser.values ser.index Ser.reindex ([...], fill_value=0) #数组的值, index of array, redefine index ser.isnull () pd.isn Ull (Ser) pd.notnull (Ser) #检测缺失数据ser. name= ser.index.name= #ser本身的名字, ser index name Ser.drop (' x ') #丢弃索引x对应的值ser +ser

. Timestamp (' 20140729 '), ' B ': PD. Series (1, Index=list (range (4))),})Print DF2# You can use Dtypes to see the data formats for each rowPrint Df2.dtypes# then look at how to view the data in the data frame and see all the dataPrint DF# Use Head to see the first few rows of data (default is the first 5 rows), but

Pandas Foundation Seriseimportas pdfromimport= Series([4-753])obj0 41 -72 53 3dtype: int64obj.valuesarray([ 4, -7, 5, 3], dtype=int64)obj.indexRangeIndex(start=0, stop=4, step=1)obj[[1,3]]# 跳着选取数据1 -73 3dtype: int64obj[1:3]1 -72 5dtype: int64pd.isnull(obj)0 False1 False2 False3 Falsedtype: bool Reindex can be used to interpolate values obj.reindex(range(5='ffill')0 41 -72 53 34 3dtype: int

label as a numpy array of Python objects Int64index Special index for integers Multiindex A hierarchical Index object that represents a multi-level index on a single axis. Can be seen as an array of tuples Datetimeindex Memory nanosecond timestamp (denoted by NumPy's Datetime64 type) Periodindex Special index for period data (t

Recently just learned this piece, if has the wrong place also invites everybody magnanimous.The python package used in this article:Ipython, Numpy, Pandas, matplotlibAncient capital's autumn original reference: Http://www.xiexingcun.com/mingjiaxiejing/302.htm1. Yu Dafu pointed out the date in the inscription at the end of the article. August 1934, in Peiping But 1934

From OPENPYXL import load_workbook import pandas as PDdata = Pd.read_excel (' test1.xlsx ', sheetname=0) # col_data = List (data.ix[:, 5]) # Gets the fifth column that starts outside the header Row_data = List (data.ix [5,:]) # Gets the fifth row of data except the header starting with writer = PD. Excelwriter (' test2.xlsx ', engine= ' OPENPYXL ') book = Load_workbook (' test2.xlsx ') writer.book = Book re

Tags: Comment processor format name fetch loop RIP today wwwWe are doing data analysis, the process of cleaning, many times will face a variety of data sources, to the different data sources for cleaning, warehousing work. Of course, Pyt