python - building panda dataframe from cloudant data, error: If using all scalar values, you must pass an index

Question

I'm just starting with pandas. All the answers I found for the error message do not resolve my error. I'm trying to build a dataframe from a dictionary constructed from an IBM cloudant query. I'm using a jupyter notebook. The specific error message is: If using all scalar values, you must pass an index

the section of code where I think my error is, is here:

def read_high_low_temp(location):
    USERNAME = "*************"
    PASSWORD = "*************"

    client = Cloudant(USERNAME,PASSWORD, url = "https://**********" )
    client.connect()


    my_database = client["temps"]
    query = Query(my_database,selector= {'_id': {'$gt': 0}, 'l':location, 'd':dt.datetime.now().strftime("%m-%d-%Y")}, fields=['temp','t','d'],sort=[{'temp': 'desc'}])
    temp_dict={}


    temp_dict=query(limit=1000, skip=5)['docs']
    df = pd.DataFrame(columns = ['Temperature','Time','Date'])
    df.set_index('Time', inplace= True)


    for row in temp_dict:
        value_list.append(row['temp'])
        temp_df=pd.DataFrame({'Temperature':row['temp'],'Time':row['t'], 'Date':row['d']}, index=['Time'])
        df=df.append(temp_df)


    message="the highest temp in the " + location + " is: " + str(max(value_list)) + " the lowest " + str(min(value_list))
return message, df

my data (Output from Jupyter) looks like this:

      Temperature      Time        Date
Time         51.6  05:07:18  12-31-2020
Time         51.6  04:59:00  12-31-2020
Time         51.5  04:50:31  12-31-2020
Time         51.5  05:15:38  12-31-2020
Time         51.5  05:03:09  12-31-2020
...           ...       ...         ...
Time         45.3  11:56:34  12-31-2020
Time         45.3  11:52:22  12-31-2020
Time         45.3  11:14:15  12-31-2020
Time         45.2  10:32:05  12-31-2020
Time         45.2  10:36:22  12-31-2020

[164 rows x 3 columns]

my full code looks like:

import numpy as np
import pandas as pd
import seaborn as sns
import os, shutil, glob, time, subprocess, re, sys, sqlite3, logging
#import RPi.GPIO as GPIO
from datetime import datetime
import datetime as dt

import cloudant
from cloudant.client import Cloudant
from cloudant.query import Query
from cloudant.result import QueryResult
from cloudant.error import ResultException

import seaborn as sns

def read_high_low_temp(location):
    USERNAME = "******"
    PASSWORD = "******"

    client = Cloudant(USERNAME,PASSWORD, url = "********" )
    client.connect()
    # location='Backyard'

    my_database = client["temps"]
    query = Query(my_database,selector= {'_id': {'$gt': 0}, 'l':location, 'd':dt.datetime.now().strftime("%m-%d-%Y")}, fields=['temp','t','d'],sort=[{'temp': 'desc'}])
    temp_dict={}


    temp_dict=query(limit=1000, skip=5)['docs']
    df = pd.DataFrame(columns = ['Temperature','Time','Date'])
    df.set_index('Time')


    for row in temp_dict:
        temp_df=pd.DataFrame({'Temperature':row['temp'],'Time':row['t'], 'Date':row['d']}, index=['Time'])
        df=df.append(temp_df)


    message="the highest temp in the " + location + " is: " + str(max(value_list)) + " the lowest " + str(min(value_list))
    return message, df

print ("Cloudant Jupyter Query test
The hour = ",dt.datetime.now().hour)


msg1, values=read_high_low_temp("Backyard")
print (msg1)

print(values)  
sns.lineplot(values)

The full error message from Jupyter is:

C:Usersustl02870AppDataLocalProgramsPythonPython37libsite-packagesseaborn\_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  FutureWarning
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-2-34956d8dafb0> in <module>
     53 
     54 #df = sns.load_dataset(values)
---> 55 sns.lineplot(values)
     56 #print (values)

~AppDataLocalProgramsPythonPython37libsite-packagesseaborn\_decorators.py in inner_f(*args, **kwargs)
     44             )
     45         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 46         return f(**kwargs)
     47     return inner_f
     48 

~AppDataLocalProgramsPythonPython37libsite-packagesseaborn
elational.py in lineplot(x, y, hue, size, style, data, palette, hue_order, hue_norm, sizes, size_order, size_norm, dashes, markers, style_order, units, estimator, ci, n_boot, seed, sort, err_style, err_kws, legend, ax, **kwargs)
    686         data=data, variables=variables,
    687         estimator=estimator, ci=ci, n_boot=n_boot, seed=seed,
--> 688         sort=sort, err_style=err_style, err_kws=err_kws, legend=legend,
    689     )
    690 

~AppDataLocalProgramsPythonPython37libsite-packagesseaborn
elational.py in __init__(self, data, variables, estimator, ci, n_boot, seed, sort, err_style, err_kws, legend)
    365         )
    366 
--> 367         super().__init__(data=data, variables=variables)
    368 
    369         self.estimator = estimator

~AppDataLocalProgramsPythonPython37libsite-packagesseaborn\_core.py in __init__(self, data, variables)
    602     def __init__(self, data=None, variables={}):
    603 
--> 604         self.assign_variables(data, variables)
    605 
    606         for var, cls in self._semantic_mappings.items():

~AppDataLocalProgramsPythonPython37libsite-packagesseaborn\_core.py in assign_variables(self, data, variables)
    666             self.input_format = "long"
    667             plot_data, variables = self._assign_variables_longform(
--> 668                 data, **variables,
    669             )
    670 

~AppDataLocalProgramsPythonPython37libsite-packagesseaborn\_core.py in _assign_variables_longform(self, data, **kwargs)
    924         # Construct a tidy plot DataFrame. This will convert a number of
    925         # types automatically, aligning on index in case of pandas objects
--> 926         plot_data = pd.DataFrame(plot_data)
    927 
    928         # Reduce the variables dictionary to fields with valid data

~AppDataLocalProgramsPythonPython37libsite-packagespandascoreframe.py in __init__(self, data, index, columns, dtype, copy)
    527 
    528         elif isinstance(data, dict):
--> 529             mgr = init_dict(data, index, columns, dtype=dtype)
    530         elif isinstance(data, ma.MaskedArray):
    531             import numpy.ma.mrecords as mrecords

~AppDataLocalProgramsPythonPython37libsite-packagespandascoreinternalsconstruction.py in init_dict(data, index, columns, dtype)
    285             arr if not is_datetime64tz_dtype(arr) else arr.copy() for arr in arrays
    286         ]
--> 287     return arrays_to_mgr(arrays, data_names, index, columns, dtype=dtype)
    288 
    289 

~AppDataLocalProgramsPythonPython37libsite-packagespandascoreinternalsconstruction.py in arrays_to_mgr(arrays, arr_names, index, columns, dtype, verify_integrity)
     78         # figure out the index, if necessary
     79         if index is None:
---> 80             index = extract_index(arrays)
     81         else:
     82             index = ensure_index(index)

~AppDataLocalProgramsPythonPython37libsite-packagespandascoreinternalsconstruction.py in extract_index(data)
    389 
    390         if not indexes and not raw_lengths:
--> 391             raise ValueError("If using all scalar values, you must pass an index")
    392 
    393         if have_series:

ValueError: If using all scalar values, you must pass an index

Answer 1

I resolved my problem with help/direction from @Ena, as it turned out I made several mistake. In layman's terms 1) I was trying to plot a tuple when it should have been a dataframe, 2) My data was in a dictionary, I was iterating through it trying to build a tuple when I should used built in panda tools to build a dataframe right from the dictionary 3) my code should have been written so as to NOT have scalar values so as NOT to need an index, and finally 4) I was trying to use a tuple as data for my seaborn plot when it should have been a dataframe. Here is the code that now works.

#!/usr/bin/env python
# coding: utf-8

import numpy as np
import pandas as pd
import seaborn as sns
import os, shutil, glob, time, subprocess, sys
from datetime import datetime
import datetime as dt
from matplotlib import pyplot as plt
import cloudant
from cloudant.client import Cloudant
from cloudant.query import Query
from cloudant.result import QueryResult
from cloudant.error import ResultException

import seaborn as sns

def read_high_low_temp(location):
    USERNAME = "****************"
    PASSWORD = "*****************"

    client = Cloudant(USERNAME,PASSWORD, url = "**************************" )
    client.connect()


    my_database = client["temps"]
    query = Query(my_database,selector= {'_id': {'$gt': 0}, 'l':location, 'd':dt.datetime.now().strftime("%m-%d-%Y")}, fields=['temp','t','d'],sort=[{'t': 'asc'}])
    temp_dict={}


    temp_dict=query(limit=1000, skip=5)['docs']

    df = pd.DataFrame(temp_dict)

    value_list=[]

    for row in temp_dict:
         value_list.append(row['temp'])

    message="the highest temp in the " + location + " is: " + str(max(value_list)) + " the lowest " + str(min(value_list))

    return message, df  

msg1, values=read_high_low_temp("Backyard")


g=sns.catplot(x='t', y='temp', data=values, kind='bar',color="darkblue",height=8.27, aspect=11.7/8.27)

print("the minimum temp is:", values['temp'].min(), " the maximum temp is:", values['temp'].max())

plt.xticks(rotation=45)

g.set(xlabel='Time', ylabel='Temperature')

plt.ylim(values['temp'].min()-1, values['temp'].max()+1)
plt.savefig("2021-01-01-temperature graph.png")
g.set_xticklabels(step=10)