The problem is your data object is a list of the DataFrames. You can either convert the DataFrames individually, e.g. df.to_csv(...) or merge them together and output as one file.
Try changing this part:
data = []
for df in path1:
df = pd.read_excel(df)
data.append(df)
data.to_csv("H:\\test1.csv", index = False)
To this:
df = pd.concat(pd.read_excel(fl) for fl in path1)
df.to_csv("H:\\test1.csv", index = False)
I've built a webscraper in python (Jupyter) to pull post content from a blog and I would like to use the csv file to create a wordcloud. This is the wordcloud code I am using:
%matplotlib notebook
from os import path
import matplotlib.pyplot as plt
import random
from wordcloud import WordCloud, STOPWORDS
# Open and read blog_stuff csv file
file = open("blog_stuff.csv",'r')
text = file.read()
file.close()
# Generate WordCloud
# !!!make sure the path for the font is correct!!!
wordcloud = WordCloud(font_path='C:/Windows/Fonts/Calibri.ttf', relative_scaling = 0.25 ).generate(text)
# Save image
plt.savefig('wordcloud.png')
# Display Image
plt.show()I keep running into an attribute error on all of the tutorials I follow. This is the error:
AttributeError Traceback (most recent call last) <ipython-input-34-20ba22870573> in <module> ----> 1 get_ipython().run_line_magic('matplotlib', 'notebook') 2 from os import path 3 import matplotlib.pyplot as plt 4 import random 5
~\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py in run_line_magic(self, magic_name, line, _stack_depth) 2305 kwargs['local_ns'] = sys._getframe(stack_depth).f_locals 2306 with self.builtin_trap: -> 2307 result = fn(*args, **kwargs) 2308 return result 2309
<C:\Users\MyName\Anaconda3\lib\site-packages\decorator.py:decorator-gen-109> in matplotlib(self, line)
~\Anaconda3\lib\site-packages\IPython\core\magic.py in <lambda>(f, *a, **k) 185 # but it's overkill for just that one bit of state. 186 def magic_deco(arg): --> 187 call = lambda f, *a, **k: f(*a, **k) 188 189 if callable(arg):
~\Anaconda3\lib\site-packages\IPython\core\magics\pylab.py in matplotlib(self, line) 97 print("Available matplotlib backends: %s" % backends_list) 98 else: ---> 99 gui, backend = self.shell.enable_matplotlib(args.gui) 100 self._show_matplotlib_backend(args.gui, backend) 101
~\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py in enable_matplotlib(self, gui) 3382 gui, backend = pt.find_gui_and_backend(self.pylab_gui_select) 3383 -> 3384 pt.activate_matplotlib(backend) 3385 pt.configure_inline_support(self, backend) 3386
~\Anaconda3\lib\site-packages\IPython\core\pylabtools.py in activate_matplotlib(backend) 311 matplotlib.rcParams['backend'] = backend 312 --> 313 import matplotlib.pyplot 314 matplotlib.pyplot.switch_backend(backend) 315
~\Anaconda3\lib\site-packages\matplotlib\pyplot.py in <module> 30 from cycler import cycler 31 import matplotlib ---> 32 import matplotlib.colorbar 33 import matplotlib.image 34 from matplotlib import rcsetup, style
~\Anaconda3\lib\site-packages\matplotlib\colorbar.py in <module> 25 26 import matplotlib as mpl ---> 27 import matplotlib.artist as martist 28 import matplotlib.cbook as cbook 29 import matplotlib.collections as collections
~\Anaconda3\lib\site-packages\matplotlib\artist.py in <module> 55 56 ---> 57 class Artist(object): 58 """ 59 Abstract base class for objects that render into a FigureCanvas.
~\Anaconda3\lib\site-packages\matplotlib\artist.py in Artist() 62 """ 63 @cbook.deprecated("3.1") ---> 64 @property 65 def aname(self): 66 return 'Artist'
~\Anaconda3\lib\site-packages\matplotlib\cbook\deprecation.py in deprecate(obj, message, name, alternative, pending, addendum) 180 pass 181 """ --> 182 183 def deprecate(obj, message=message, name=name, alternative=alternative, 184 pending=pending, obj_type=obj_type, addendum=addendum):
AttributeError: 'property' object has no attribute 'name'
Would any of you fine folks know how I can remedy this issue?
Edit: Removed my name from path
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Hi, how did you install matplotlib? Was it a conda installation? And which version of Matplotlib are you running on? Try upgrading it to the latest 3.2.1 version and run the program :)
python - Matplotlib returning: AttributeError: 'property' object has no attribute '__name__' - Stack Overflow
python - AttributeError: 'property' object has no attribute - Stack Overflow
django - Python "property object has no attribute" Exception - Stack Overflow
python - AttributeError: 'str' object has no attribute 'csv' - Stack Overflow
The problem is your data object is a list of the DataFrames. You can either convert the DataFrames individually, e.g. df.to_csv(...) or merge them together and output as one file.
Try changing this part:
data = []
for df in path1:
df = pd.read_excel(df)
data.append(df)
data.to_csv("H:\\test1.csv", index = False)
To this:
df = pd.concat(pd.read_excel(fl) for fl in path1)
df.to_csv("H:\\test1.csv", index = False)
your problem is that you have a list of data frames and you are calling to_csv on the whole list instead of the individual data frames. Two options here, if the list only has one data frame in it, use this code:
data[0].to_csv("H:\\test1.csv", index = False)
if it has multiple data frames in it, do this:
for i in data:
i.to_csv("filename", index = False)
bear in mind that for the second option you will need to make your filenames dynamic to avoid overwriting.
EDIT:
Misread your question. You need to actually merge the data frames
df1 = pd.read_excel(path1)
df2 = pd.read_execl(path2)
df = df1.merge(df2, how = 'inner', on = 'JoinField')
df.to_csv("H:\\test1.csv", index = False)
In addition to needing to inherit from object, properties only work on instances.
a = A()
a.db.doSomething("blah")
To make a property work on the class, you can define a metaclass. (A class is an instance of a metaclass, so properties defined on the metaclass work on the class, just as properties defined on a class work on an instance of that class.)
You aren't using classes correctly. A class is (normally) two things:
- A factory for creating a family of related objects
- A definition of the common behaviour of those objects
These related objects are the instances of the class. Normal methods are invoked on instances of the class, not on the class itself. If you want methods that can be invoked from the class, without an instance, you need to label the methods with @classmethod (or @staticmethod).
However I don't actually know whether properties work when retrieved from a class object. I can't check right now, but I don't think so. The error you are getting is that A.db is retrieving the property object which defines the property itself, it isn't "evaluating" the property to get A.__db. Property objects have no doSomething attribute. Properties are designed to be created in classes as descriptions of how the instances of those classes work.
If you did intend to be working with an instance of A, then you'll need to create one:
my_a = A()
my_a.db.doSomething("blah")
However, this will also fail. You have not correctly written getDB as any kind of method. Normal methods need an argument to represent the instance it was invoked on (traditionally called self):
def getDB(self):
...
Static methods don't, but need a decorator to label them as static:
@staticmethod
def getDB():
...
Class methods need both an argument to receive the class they were invoked on, and a decorator:
@classmethod
def getDB(cls):
...
How do I fix this error, please?
Code:
import pandas as pd
import numpy as np
import itertools
import csv
data = pd.ExcelFile(r"C:\Users\Josh-\OneDrive\Documents\Prem Tipster\YouTube Files\FPL Documents\FPL Tools.xlsx")
df = pd.read_excel(data, 'Defence')
#Drop columns and rows
df = df.drop(df.columns[[0, 1]], axis=1)
df = df.iloc[21:]
df = df.dropna(how= "all", axis=1)
#New headers for columns and rows
df.columns = df.iloc[0]
df = df.iloc[1:]
df.index = ['Row_1']
index = list(df.columns[[0]])
df = df.set_index(index)
#Remove spaces from column names
df.columns = df.columns.str.replace(' ', '')
DEF_IN_SQUAD = 2
DEF_IN_XI = 1
STARTING_GW = 1
ENDING_GW = 19
def validCombinations(GAMEWEEK):
TOTAL_COMB = list(itertools.combinations(df[GAMEWEEK], DEF_IN_SQUAD))
VALID_COMB = [(sum(sorted(x)[:DEF_IN_XI])) for x in TOTAL_COMB]
return(VALID_COMB)
TEAM_COMB = df.columns
for i in range(STARTING_GW, ENDING_GW, 1):
GW = "GW{}".format(i)
a = validCombinations(GW)
# print(len(a))
TEAM_COMB = TEAM_COMB.insert(i, a)
TEAM_COMB.to_csv(r"C:\Users\Josh-\OneDrive\Documents\Prem Tipster\Python\FPL Data Analysis\Defence Rotations Data.csv", sep='\t', index=False)
to_csv is a method of a DataFrame object, not of the pandas module.
df = pd.DataFrame(CV_data.take(5), columns=CV_data.columns)
# whatever manipulations on df
df.to_csv(...)
You also have a line pd.DataFrame(CV_data.take(5), columns=CV_data.columns) in your code.
This line creates a dataframe and then discards it. Even if you were successfully calling to_csv, none of your changes to CV_data would have been reflected in that dataframe (and therefore in the outputed csv file).
Solution- You should write df.to_csv instead of pd.to_csv
Justification- to_csv is a method to an object which is a df (DataFrame); while pd is Panda module.
Hence, your code was not working and throwing this Error " AttributeError: module 'pandas' has no attribute 'to_csv'"
I am trying to use pandas to create a CSV of the historical data from coinmarketcap. Just this simple code fails and I can't seem to find the answer on the web at all. Any help is greatly appreciated.
import pandas as pd
df = pd.read_html('https://coinmarketcap.com/currencies/bitcoin/historical-data/?start=20130428&end=20170812')
df.to_csv('test.csv')File "test.py", line 3, in <module>
df.to_csv('test.csv')
AttributeError: 'list' object has no attribute 'to_csv'
The other solutions are not working because your data does not have the correct structure for a DataFrame. You need to access the lists of dicts from the top level keys first.
import pandas
df1 = pandas.DataFrame(diff['added'])
df1['change'] = 'added'
df2 = pandas.DataFrame(diff['removed'])
df2['change'] = 'removed'
df = df1.append(df2)
df.to_csv('diff.csv')
Change per Comment Request
df1 = pandas.read_csv('list1.csv')
df1['version'] = 'list1'
df2 = pandas.read_csv('list2.csv')
df2['version'] = 'list2'
# keep only columns 'version', 'ean', 'price'
diff = df1.append(df2)[['version', 'ean', 'price']]
# keep only duplicated eans, which will only occur
# for eans in both original lists
diff = diff[diff['ean'].duplicated(keep=False)]
# perform a pivot https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html
diff = diff.pivot(index='ean', columns='version', values='price')
# back to a normal dataframe
diff = diff.reset_index()
diff.columns.name = None
# rename columns and keep only what we want
diff = diff.rename(columns={'list1': 'price1', 'list2': 'price2'})[['ean', 'price1', 'price2']]
diff['difference'] = diff['price2'] - diff['price1']
you can use to_csv method that's being provided by pandas :
import pandas as pd
df = pd.DataFrame(dict([ (k,pd.Series(v)) for k,v in diff.items() ]))
df.to_csv('diff.csv')
the read_html() method returns a list of dataframes, not a single dataframe:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_html.html
You'll want to loop through your df_list and run to_csv on each entry, like so:
import pandas as pd import requests
query_set = ["points-per-game"]
for query in query_set:
url = 'https://www.teamrankings.com/ncaa-basketball/stat/' + str(query)
html = requests.get(url).content
df_list = pd.read_html(html)
print(df_list)
for current_df in df_list:
current_df.to_csv(str(query) + "stat.csv", encoding="utf-8")
print(current_df)
The function pd.read_html returns a list of DataFrames found in the HTML source. Use df_list[0] to get the DataFrame which is the first element of this list.