Files
sivasPrices/lib/test.py
T

25 lines
1.0 KiB
Python

import pandas as pd
from io import StringIO
#df1 = pd.DataFrame({'Teilenummer': ['709000031_A', '825304002', '825304003', '825304004', '825304006', '825304007', '825304008', '0_A3000020'],
#'Laufende Materialkosten': [43.22, 26.19, 30.49, 25.85, 32.35, 23.99, 19.25, 0] })
#df2 = pd.DataFrame({'Teilenummer':['825304002', '709000031_A']})
df1 = pd.read_json(
'''{"Teilenummer":{"0":"709000031_A","1":"825304002","2":"825304003","3":"825304004","4":"825304006","5":"825304007","6":"825304008","7":"0_A3000020"},
"Laufende Materialkosten":{"0":43.22,"1":26.19,"2":30.49,"3":25.8547,"4":32.3574812376,"5":23.99,"6":19.25,"7":null}}'''
)
df2 = pd.read_json(
'''{"Teilenummer":{"0":825304002,"1":"709000031_A"}}'''
)
print(df1.dtypes)
print(df2.dtypes)
df1['Teilenummer'] = df1['Teilenummer'].astype(str)
df2['Teilenummer'] = df2['Teilenummer'].astype(str)
print(df1.dtypes)
print(df2.dtypes)
#print(df1)
#print(df2)
#print(df1.to_json())
#print(df2.to_json())
newdf = df1.merge(df2, on='Teilenummer', how='inner')
print(newdf)