Create a pd.Series from data

Many ways to create a Series from data

1. From a one-dimensional list. Example. Create a Series from a tuple, range, or np.ndarray the same way.
2. From a list of two-item lists. The first column specifies the index. Example.
3. From a dict. The keys of the dict specify the index. Example.
4. Create a Series holding multiple copies of the same value.

   import sys
   import numpy as np
   import pandas as pd
   
   #Series born holding 10 zeros.
   #Must specify a range so the computer knows how many zeros.
   
   series = pd.Series(data = 0, index = np.arange(10))
   print(series)
   
   sys.exit(0)
   

   0    0
   1    0
   2    0
   3    0
   4    0
   5    0
   6    0
   7    0
   8    0
   9    0
   dtype: int64
   

5. Create an empty Series, and then append rows to it.

   import sys
   import numpy as np
   import pandas as pd
   
   series = pd.Series(dtype = np.int64)   #Start with an empty Series.
   print(series)
   print()
   
   series.loc[0] = 10
   print(series)
   print()
   
   s = pd.Series(data = [20, 30], index = [1, 2])
   series = series.append(s)
   print(series)
   
   sys.exit(0)
   

   Series([], dtype: int64)
   
   0    10
   dtype: int64
   
   0    10
   1    20
   2    30
   dtype: int64
   

6. Create a copy of an existing Series. In the following program, series0 and series1 share the same data. They are merely two different views of the same data.

   import sys
   import pandas as pd
   
   series0 = pd.Series(data = [10, 20, 30], name = "series0")
   print(series0)
   print()
   
   series1 = pd.Series(data = series0, name = "series1")
   series1[0] = 11   #Warning: changes series0.
   print(series0)
   print()
   
   series2 = series0.copy()
   series2.name = "series2"
   series2[1] = 21   #Does not change series0.
   print(series0)
   
   sys.exit(0)
   

   0    10
   1    20
   2    30
   Name: series0, dtype: int64
   
   0    11
   1    20
   2    30
   Name: series0, dtype: int64
   
   0    11
   1    20
   2    30
   Name: series0, dtype: int64
   

7. Read a Series from a text file containing one or two columns.

   import sys
   import pandas as pd
   
   url = "http://oit2.scps.nyu.edu/~meretzkm/pandas/series/infile1.txt"
   df = pd.read_csv(url, header = None) #Create a pd.DataFrame containing one column numbered 0
   series = df[0]                       #Get that column.
   print(series)
   sys.exit(0)
   

   0    10
   1    20
   2    30
   3    40
   4    50
   Name: 0, dtype: int64
   

   import sys
   import pandas as pd
   
   url = "http://oit2.scps.nyu.edu/~meretzkm/pandas/series/infile2.csv"
   df = pd.read_csv(url, index_col = "day") #Create a pd.DataFrame containing one column named "temperature".
   series = df["temperature"]               #Get that column.
   print(series)
   sys.exit(0)
   

   day
   1    10.0
   2    20.0
   3    30.0
   4    40.0
   5    50.0
   Name: temperature, dtype: float64