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I am new to pandas and I have been struggling how to use pivot function.
I am trying to make the index as flat_type.
When I tried to use the pivot function, I kept getting this error:
TypeError: pivot() got multiple values for argument 'index'
And I have no idea how to fix it.
Any help or suggesttion would do greatly.! thankyou have a nice day!
link to dataset: https://data.gov.sg/dataset/median-rent-by-town-and-flat-type
code:
import pandas as pd
import numpy as np
df = pd.read_csv('median-rent-by-town-and-flat-type (1).csv',na_values=['na','-'])
mydf = df.dropna()
mydf = mydf.reset_index()
mydf.pivot(mydf,index="flat_type",columns="town",values="median_rent")
Remove mydf from pivot in paratheses, because already chained mydf with DataFrame.pivot method:
mydf.pivot(index="flat_type",columns="town",values="median_rent")
Another solution is use pandas.pivot - then is changed mydf.pivot to pd.pivot:
pd.pivot(mydf, index="flat_type",columns="town",values="median_rent")
Try my removing df
mydf.pivot(index="flat_type", columns="town", values="median_rent")
Thank you.
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I am running Jupyter notebook with Python 3.0 using Pandas to read from an Excel file. I am using a converter to change values in columns i.e. -1 to 1. I keep getting a syntax error in the converters.
import pandas as pd
def convert_adult(cell):
if cell==-1:
return 1
return cell
df = pd.read_excel("Merged.xlsx", "Sheet1", converters = ['adult_not_activation':convert_adult])
return is
File "<ipython-input-17-8eea921e19bb>", line 10
df = pd.read_excel("Merged.xlsx", "Sheet1", converters = ['adult_not_activation':convert_adult])
^
SyntaxError: invalid syntax
I am in the beginning of my journey in Python and Pandas so I hope my problem is not too trivial to ask. Cheers
The error points you to the problem :) You are using a list where a dict is expected.
df = pd.read_excel("Merged.xlsx", "Sheet1", converters = {'adult_not_activation': convert_adult})
converters argument takes a dictionary, You are giving this dictionary as a list but with dictionary syntax.
df = pd.read_excel("Merged.xlsx", "Sheet1", converters = {'adult_not_activation':convert_adult}) # {} instead of []
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For the first time, I'm unable to use the .shift() method on a column of the DataFrame I'm working with, giving me a DataFrame' object is not callable error.
sdf = quandl.get("AAII/AAII_SENTIMENT", authtoken="mytoken")
sdf = pd.DataFrame(data = sdf)
sdf = sdf.infer_objects()
sdf.index = pd.to_datetime(sdf.index, dayfirst=True)
sdf = sdf.iloc[9:,]
sdf['sp500_2w_future_close'] = sdf(['S&P 500 Weekly Close']).shift(-2)
I was expecting to get a new column displaying S&P 500 Weekly Close two rows down and instead got this weird error. He, p please!
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I am a Python novice and need help. I tried searching, but couldn't find posts relevant to what I need.
I have a data frame containing a column called diet which contains many similar values like 'Only Vegetarian', 'Mostly Vegetarian', 'Strictly Vegetarian', 'Veggie' etc. How do I combine these values into a single value called say 'Vegetarian'?
import pandas as pd
import numpy as np
df1 = pd.DataFrame({'col1': ['Only Vegetarian', 'Mostly Vegetarian', 'Strictly Vegetarian', 'Veggie','Meat']})
df1['col2'] = np.where(df1.col1.str.contains('Vege'), 'Vegeterian', 'Not Vegeterian')
You can make a dummy variable by encoding your rule in a function and using pd.Series.apply
def check_veg(x):
# The elipse below signifies you providing all the values somehow
if x in ["Veggie", "Mostly Vegetarian", ...]:
return 1
else:
return 0
df["isVeg"] = df["diet"].apply(check_veg)
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I have to set the result of
df.groupby(['région'])['counts'].sum())
as the column c2 of my dataframe.
So I do this:
df['c2'] = pd.to_numeric(df.groupby(['région'])['counts'].sum()).astype(float)
Thus
pd.to_numeric(df.groupby(['région'])['counts'].sum()).astype(float)
has type float, and so df['c2'] should also have type float.
However, when I tried to print the column of my dataframe df['c2'] all values are NaN.
How can I solve this?
EDIT 1:
My code is here
In your code, after this part:
import numpy as np
d_copy = d.copy()
Do this:
d_copy['counts2'] = d_copy.groupby(['region'])['counts'].transform('count')
Results:
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I need to look up a value in a csv file given a criteria in a function. When I run my program I get all the values but not the one associated with my entry. Any help will be appreciated.
The date looks something like this:
rose,7.95
lily,3.95
begonia,5.95
The function I created is:
def problem3_8(csv_pricefile, flower):
import csv
archivo = open(csv_pricefile)
for row in csv.reader(archivo):
if flower in row[0]:
print(row[1])
archivo.close()
When I ran the program using the next line:
problem3_7("flowers.csv","rose")
I get all the value in the file, like this:
7.95
3.95
5.95
But the answer should be just the value associated with the second entry.
7.95
Thanks
I ran your code given and had the correct output of 7.95.
Is it possible you called the wrong function? In your question you referred to the function problem3_7 instead of the function problem3_8