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{'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.
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]]
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
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