Iam using rpy2 to get comorbidity Index of patients , i got the results but iam not able to convert those output to pandas Dataframe
below is the code
#creating Datframe
data = {"person_id":[1,1,1,2,2,3],
"dx_1":["F11","E40","","F32","C77","G10"],
"dx_2":["F1P","E400","","F322","C737",""]}
#converting Pandas Dataframe to R Datframe using rpy2
import rpy2
from rpy2.robjects import pandas2ri
import rpy2.robjects.numpy2ri
from rpy2.robjects.packages import importr
r_dataframe = pandas2ri.py2ri(df1)
print(r_dataframe)
#installing 'comorbidity ' package using rpy2
R = rpy2.robjects.r
DTW = importr('comorbidity')
#executing comorbidity function by using one column icd_1
output = DTW.comorbidity(x = r_dataframe, id = "person_id", code = "icd_1",
score = "charlson", assign0 = False,
icd = "icd10")
print(output)
but not able to convert output to pandas dataframe
import rpy2, rpy2.robjects as robjects, rpy2.robjects.packages as rpackages
from rpy2.robjects.vectors import StrVector
#Converting data frames back and forth between rpy2 and pandas
from rpy2.robjects import r, pandas2ri
#convert output to pandas dataframe
pandas2ri.ri2py_dataframe(output)
getting below error
TypeError: Parameter 'categories' must be list-like, was
please help
Thanks in advance
Related
My dtype is changing after i unhash the foo and groupby i get # we require a list, but not a 'str'.
I wanted if the value (in my case Date) in the 1 column is the same then the text from the 3 column goes there after a ',' sign, in my final project
import os
import pandas as pd
import dateutil
from pandas import DataFrame
from datetime import datetime, timedelta
data_file_folder = '.\Data'
df = []
for file in os.listdir(data_file_folder):
if file.endswith('.xlsx'):
print('Loading File {0}...'.format(file))
df.append(pd.read_excel(os.path.join(data_file_folder,file),sheet_name='Sheet1'))
df_master = pd.concat(df,axis=0)
df_master['Date'] = df_master['Date'].dt.date
#foo = lambda a: ", ".join(a)
#df_master = df_master.groupby(by='Date').agg({'Tweet': foo}).reset_index()
#df_master.to_excel('.\NewFolder\example.xlsx',index=False)
#df_master
using pandas and try to resample
index = pd.date_range('1/1/2000', periods=9, freq='T')
series = pd.Series(range(9), index=index)
series.resample('3T').mean()
getting:
ImportError: cannot import name 'ResamplerWindowApply' from 'pandas.core.apply' (C:\Users\XXX\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\apply.py)
any hint??
I want to concat multiple pandas DataFrames using a function. For example, see the following.
import pandas as pd
import numpy as np
df =pd.DataFrame({'A':['Apple','Yahoo','Google']})
df2 =pd.DataFrame({'A':['Microsoft', 'Apple', 'Google']})
nan_value = 0
combined = pd.concat(dfs, join='outer').fillna(nan_value)
But, when I try to put the same in to a function as the following it gives an error: "TypeError: first argument must be an iterable of pandas objects, you passed an object of type "DataFrame".
def combine_dataframes(df):
nan_value = 0
combined = pd.concat(df, join='outer').fillna(nan_value)
return combined
dfs = [df, df2]
combined = [combine_dataframes(i) for i in dfs]
i need to read a string like csv content with pandas , but pandas get some errors, i don't knonw what happened, can anyone help me?
import pandas as pd
import io
s = ',测试项,信息,结果\r\n0,软件测试机型805,软件测试机型805,PASS\r\n1,软件当前版本1,软件当前版本1,FAIL\r\n2,软件测试机型805,软件测试机型805,PASS\r\n3,软件当前版本1,软件当前版本1,FAIL\r\n4,软件测试机型805,软件测试机型805,PASS\r\n5,软件当前版本1,软件当前版本1,FAIL\r\n'
buf = io.StringIO()
buf.write(s)
df = pd.read_csv(buf)
got error, EmptyDataError: No columns to parse from file
老铁你拿去
import pandas as pd
import io
s = ',测试项,信息,结果\r\n0,软件测试机型805,软件测试机型805,PASS\r\n1,软件当前版本1,软件当前版本1,FAIL\r\n2,软件测试机型805,软件测试机型805,PASS\r\n3,软件当前版本1,软件当前版本1,FAIL\r\n4,软件测试机型805,软件测试机型805,PASS\r\n5,软件当前版本1,软件当前版本1,FAIL\r\n'
buf = io.StringIO()
buf.write(s)
buf.seek(0)
df = pd.read_csv(buf)
``
Does anyone know how one goes about enabling the REFS_OK flag in numpy? I cannot seem to find a clear explanation online.
My code is:
import sys
import string
import numpy as np
import pandas as pd
SNP_df = pd.read_csv('SNPs.txt',sep='\t',index_col = None ,header = None,nrows = 101)
output = open('100 SNPs.fa','a')
for i in SNP_df:
data = SNP_df[i]
data = np.array(data)
for j in np.nditer(data):
if j == 0:
output.write(("\n>%s\n")%(str(data(j))))
else:
output.write(data(j))
I keep getting the error message: Iterator operand or requested dtype holds references, but the REFS_OK was not enabled.
I cannot work out how to enable the REFS_OK flag so the program can continue...
I have isolated the problem. There is no need to use np.nditer. The main problem was with me misinterpreting how Python would read iterator variables in a for loop. The corrected code is below.
import sys
import string
import fileinput
import numpy as np
SNP_df = pd.read_csv('datafile.txt',sep='\t',index_col = None ,header = None,nrows = 5000)
output = open('outputFile.fa','a')
for i in range(1,51):
data = SNP_df[i]
data = np.array(data)
for j in range(0,1):
output.write(("\n>%s\n")%(str(data[j])))
for k in range(1,len(data)):
output.write(str(data[k]))
If you really want to enable the flag, I have an working example.
Python 2.7, numpy 1.14.2, pandas 0.22.0
import pandas as pd
import numpy as np
# get all data as panda DataFrame
data = pd.read_csv("./monthdata.csv")
print(data)
# get values as numpy array
data_ar = data.values # numpy.ndarray, every element is a row
for row in data_ar:
print(row)
sum = 0
count = 0
for month in np.nditer(row, flags=["refs_OK"], op_flags=["readwrite"]):
print month