Filtering Pandas Dataframe using OR statement
From the docs:
Another common operation is the use of boolean vectors to filter the data. The operators are: | for or, & for and, and ~ for not. These must be grouped by using parentheses.
http://pandas.pydata.org/pandas-docs/version/0.15.2/indexing.html#boolean-indexing
Try:
alldata_balance = alldata[(alldata[IBRD] !=0) | (alldata[IMF] !=0)]
You can do like below to achieve your result:
import seaborn as snsimport matplotlib.pyplot as pltimport pandas as pdimport numpy as np........#use filter with plot#orfg=sns.factorplot('Retailer country', data=df1[(df1['Retailer country']=='United States') | (df1['Retailer country']=='France')], kind='count')fg.set_xlabels('Retailer country')plt.show()#also#andfg=sns.factorplot('Retailer country', data=df1[(df1['Retailer country']=='United States') & (df1['Year']=='2013')], kind='count')fg.set_xlabels('Retailer country')plt.show()