I have been trying to build a multi-page Dash app based on how nedned had mentioned in Splitting callback definitions in multiple files. My directory structure pretty much follows the same blueprint:
run.py
project/
__init__.py
app.py
server.py
callbacks1.py
tab1_layout.py
tab1_callbacks.py
wsgi.py
app.py is like an index file that has an overarching layout for the dashboard. The dashboard’s contents are to be split across tabs, for which I decided to split the code across files dedicated to those tabs’ contents, and corresponding files for dedicated callbacks (like tab1_layout.py and tab1_callbacks.py).
The problem started when I tried to write a callback with some pandas dataframe manipulation/calculation in tab1_layout.py. And it was simple slicing using iloc/loc. For some reason, it is throwing me a positional-index-out-of-bounds error when I am facing no such problem with the same operations in a Jupyter notebook or even a standalone vanilla python file.
Other than listing through iloc/loc, I tried out two other methods to calculate dff which worked:
########### different ways to calculate dff ###########
# direct listing using iloc
dff = dff_buff.iloc[[0, 1, 2, 4, 5, 25, 56]].reset_index(drop=True)
# chaining using append() from Pandas
chain_1 = dff_buff.iloc[0:3].append(dff_buff.iloc[4:6])
chain_2 = chain_1.append(dff_buff.iloc[25:26])
dff = chain_2.append(dff_buff.iloc[56:57])
# reset_index() without dropping and filtering based on old index
dff_buff_1 = dff_buff.reset_index()
dff = dff_buff_1[(dff_buff_1['index'] == 0)
| (dff_buff_1['index'] == 1)
| (dff_buff_1['index'] == 2)
| (dff_buff_1['index'] == 4)
| (dff_buff_1['index'] == 5)
| (dff_buff_1['index'] == 25)
| (dff_buff_1['index'] == 56)]
#######################################################
However, even after this, Dash throws a callback error (KeyError: None) at the sum(axis=1) function, which led me to think that perhaps that iloc/loc mess-up is something I cannot ignore.
For reference (data at: https://github.com/darkreqnx/sales_file):
import numpy as np
import pandas as pd
xlsx = pd.ExcelFile('./data/sales_data.xlsx')
df_oper = pd.read_excel(xlsx, 'oper')
states_list = list(df_oper)[2:]
months_list = list(df_oper.month.value_counts(dropna=False).reset_index()['index'])
month_selected = 'Sep-15'
districts_selected = ['district_1', 'district_6']
op_tb1 = pd.DataFrame([], columns=['Quick figures'])
op_tb2 = pd.DataFrame([], columns=['No of units sold'])
dff_buff = df_oper[df_oper.month == month_selected].reset_index(drop=True)
#######################################################
# calculate dff
#######################################################
df1 = dff.copy()
df1['sales_metric'][0] = 'Primary Sales'
df1['sales_metric'][1] = 'Returned Sales'
df1['sales_metric'][2] = 'Accepted Sales'
df1['sales_metric'][3] = 'Net Sales'
df1['sales_metric'][4] = 'Invalid Sales'
df2 = df1.iloc[0:5]
df2['district_6'][2] = df1['district_6'].iloc[6]
df2['district_6'][3] = df1['district_6'].iloc[5]
df2['district_6'][4] = df1['district_6'].iloc[6] - df1['district_6'].iloc[5]
op_tb1['Quick figures'] = df2['sales_metric']
op_tb2['No of units sold'] = df2[districts_selected].sum(axis=1)
print(op_tb1)
print(op_tb2)
tr_breaker = input("\nend of code block check")
Another interesting thing I found was that the positional index error wasn’t thrown when I used iloc in an iloc[start:stop] manner, instead of an iloc[i1, i2, i3, …]. Can somebody please help me understand where I am going wrong with iloc/loc, and also help resolve the issue with the sum() function?
Error due to iloc/iloc: error_1
and error at sum(axis=1): error_2
