Tag: Pandas

Snippet 1 pd.set_option(‘display.max_columns’, None) pd.set_option(‘display.max_rows’, None) Snippet 2 pd.set_option(‘max_columns’, None) Snippet 3 pd.options.display.max_columns = None pd.options.display.max_rows = None Similar Snippets Pandas Select All Columns Except One Code Example – pandas How To Drop Columns In Pandas Code Example – pandas Dictionary To A Dataframe Pandas Arrays Must All Be Same Length Code Example – pandas… Continue reading See All Columns Pandas Code Example

Snippet 1 df[df[‘col’].isnull()] Copyright © Code Fetcher 2020    

Snippet 1 # Select rows 0, 1, 2 (row 3 is not selected) surveys_df[0:3] Snippet 2 # iloc[row slicing, column slicing] surveys_df.iloc[0:3, 1:4] Copyright © Code Fetcher 2020    

Snippet 1 Specifically, .loc[] allows you to select all rows with an index lexicographically using slice notation. This works only if the index is sorted (.sort_index()). Copyright © Code Fetcher 2020    

Snippet 1 df= pandas.read_csv(“file.csv”,header= None) df_2= df.iloc[(df.loc[df[0]==’report field’].index[0]+1):, :].reset_index(drop = True) Copyright © Code Fetcher 2020    

Snippet 1 pip install pandas Copyright © Code Fetcher 2020    

Snippet 1 df_dict = pandas.read_excel(‘ExcelFile.xlsx’, header=[0, 1], sheetname=None) Snippet 2 import pandas as pd sheet1, sheet2 = None, None with pd.ExcelFile(“PATHFileName.xlsx”) as reader: sheet1 = pd.read_excel(reader, sheet_name=’Sheet1′) sheet2 = pd.read_excel(reader, sheet_name=’Sheet2′) Copyright © Code Fetcher 2020    

Snippet 1 In [60]: df[‘Country’].str.normalize(‘NFKD’).str.encode(‘ascii’, errors=’ignore’).str.decode(‘utf-8’) Out[60]: 0 Aland Islands 1 Aland Islands 2 Albania 3 Albania 4 Albania Name: Country, dtype: object Snippet 2 df[‘Country’] = df[‘Country’].str.replace(u”Å”, “A”) df[‘City’] = df[‘City’].str.replace(u”ë”, “e”) Copyright © Code Fetcher 2020    

Snippet 1 pd.read_html(‘https://finance.yahoo.com/quote/TSLA/profile?p=TSLA’)[0] Copyright © Code Fetcher 2020    

Snippet 1 # A useful rule of thumb is to use the simplest data structure that still # satisfies your needs. If we rank the data structures from most simple # to least simple, it usually ends up like this: 1. Dictionaries / lists 2. Numpy arrays 3. Pandas series / dataframes # See source… Continue reading Python When To Use Pandas Series, Numpy Ndarrays Or Simply Python Dictionaries Code Example

Snippet 1 import sys import csv import glob import pandas as pd # get data file names path =r’C:DRODCL_rawdata_filesexcelfiles’ filenames = glob.glob(path + “/*.xlsx”) dfs = [] for df in dfs: xl_file = pd.ExcelFile(filenames) df=xl_file.parse(‘Sheet1’) dfs.concat(df, ignore_index=True) Snippet 2 import os import pandas as pd import openpyxl as excel import glob #setting up path path… Continue reading Pandas Reading Each Xlsx File In Folder Code Example