PYTHON

pandas from series to dataframe

#To convert a series to a dataframe simply apply the to_frame() method
#to the series
s.to_frame() 

pandas.core.series.series to dataframe

>>> s = pd.Series(["a", "b", "c"],
...               name="vals")
>>> s.to_frame()
  vals
0    a
1    b
2    c

pd df to series

import pandas as pd

data = {'First_Name': ['Jeff','Tina','Ben','Maria','Rob']}
df = pd.DataFrame(data, columns = ['First_Name'])

print(df)
#	First_Name
#0       Jeff
#1       Tina
#2        Ben
#3      Maria
#4        Rob

print(type(df))
# <class 'pandas.core.frame.DataFrame'>

df = df.squeeze() # <- Converts to a pandas series
print(df)
#0     Jeff
#1     Tina
#2      Ben
#3    Maria
#4      Rob
#Name: First_Name, dtype: object

print(type(df))
# <class 'pandas.core.series.Series'>

series.Series to dataframe

df = pd.DataFrame([s])
print (df)
         product_id_y  count
6159402       1159730      1

pandas dataframe to series

df.squeeze() # converts to series
# OR
# When loading a file
pd.read_csv("df.csv", index_col="col1", squeeze=True) 

pandas dataframe to series

series = df.squeeze() # Convert df to series

series to dataframe

pd.DataFrame({'email':sf.index, 'list':sf.values})

convert series to dataframe pandas

In [119]:

common = df1.merge(df2,on=['col1','col2'])
print(common)
df1[(~df1.col1.isin(common.col1))&(~df1.col2.isin(common.col2))]
   col1  col2
0     1    10
1     2    11
2     3    12
Out[119]:
   col1  col2
3     4    13
4     5    14