let us suppose that we have following table :
Kakheti Tbilisi Shida Kartli Kvemo Kartli Samtskhe-Javakheti \
1 447.773080 695.168755 575.344860 492.989720 …
2 368.175479 680.922659 449.687764 428.683988 …
3 94.253356 381.434387 147.149448 219.399642 …
4 38.283124 77.261457 39.516685 29.104063 …
5 71.281052 0.720206 74.027796 49.294079 …
6 1.463107 15.452695 2.457914 0.000000 …
as you see one column contains ... symbol, i have tried following code :
import pandas as pd
data =pd.read_excel("https://geostat.ge/media/45425/106_Distribution-of-average-monthly-incomes-per-household-by-regions.xls",
skiprows=[0])
data.drop(["Unnamed: 0","Other regions**","Georgia"],axis=1,inplace=True)
data.dropna(axis=0,how='all',inplace=True)
data.dropna(axis=1,how='all',inplace=True)
for column in data.columns:
if data[column].dtype=="object":
data[column] =data[column].str.strip()
data = data[data.columns.drop(list(data.filter(regex='…')))]
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', 165)
print(data.head(100))
special attention is dedicated to given line
data = data[data.columns.drop(list(data.filter(regex='…')))]
dropna also does not work,so what might be optimal variant?
Edited: come on guys(whoever closed this question) , it is not about display all columns, it is about showing specific columns, here is what i found :
data =data._get_numeric_data()
result is :
Kakheti Tbilisi Shida Kartli Kvemo Kartli Adjara A.R. \
1 447.773080 695.168755 575.344860 492.989720 656.011810
2 368.175479 680.922659 449.687764 428.683988 576.822184
3 94.253356 381.434387 147.149448 219.399642 289.083094
4 38.283124 77.261457 39.516685 29.104063 112.680109
5 71.281052 0.720206 74.027796 49.294079 17.850210
6 1.463107 15.452695 2.457914 0.000000 4.489037
