first argument must be an iterable of pandas objects, you passed an object of type "Series&quot-CodePudding

I have the following dataframe:

s = df.head().to_dict()
print(s)

{'BoP transfers': {1998: 12.346282212735618,
  1999: 19.06438060024298,
  2000: 18.24888031473687,
  2001: 24.860019912667006,
  2002: 32.38242225822908},
 'Current balance': {1998: -6.7953,
  1999: -2.9895,
  2000: -3.9694,
  2001: 1.1716,
  2002: 5.7433},
 'Domestic demand': {1998: 106.8610389799729,
  1999: 104.70302507466538,
  2000: 104.59254229534136,
  2001: 103.83532232336977,
  2002: 102.81709401489702},
 'Effective exchange rate': {1998: 88.134,
  1999: 95.6425,
  2000: 99.927725,
  2001: 101.92745,
  2002: 107.85565},
 'RoR (foreign liabilities)': {1998: 0.0433,
  1999: 0.0437,
  2000: 0.0542,
  2001: 0.0539,
  2002: 0.0474}}

which can be transformed back to its original form using

df = pd.DataFrame.from_dict(s)

I want to slice this dataframe in the following manner:

df_1 = df.iloc[:,0:2]
df_2 = pd.concat(df.iloc[:,0], df.iloc[:,3:])

when I get the titled error. I know there are some questions regarding this already, but I am unable to put the pieces together. Specifically, in my case, the dataframe is not this small (it has 100 columns). I want something along the lines of

df_1 = df.iloc[:,0:10]
df_2 = pd.concat(df.iloc[:,0], df.iloc[:,11:20])
df_3 = pd.concat(df.iloc[:,0], df.iloc[:,21:30])

and so on. How can this be accomplished? Thank you.

CodePudding user response：

You need to use a list of the DataFrames to merge and to concat on axis=1:

df_2 = pd.concat([df.iloc[:,0], df.iloc[:,3:]], axis=1)

Or, better, use slicing:

df_2 = df.iloc[:, [0,3,4]]
# or
df_2 = df.iloc[:, np.r_[0,3:df.shape[1]]]

Output:

      BoP transfers  Effective exchange rate  RoR (foreign liabilities)
1998      12.346282                88.134000                     0.0433
1999      19.064381                95.642500                     0.0437
2000      18.248880                99.927725                     0.0542
2001      24.860020               101.927450                     0.0539
2002      32.382422               107.855650                     0.0474