I'd like to grade in Korab.
So first of all right now
from google.colab import files
uploaded = files.upload()
for fn in uploaded.keys():
print('User uploaded file "{name}" with length {length} bytes'.format(
name=fn, length=len(uploaded[fn])))
Load files with this.
import pandas as pd
wordtest = pd.read_csv('/content/test (response) - 11.csv')
wordtest
I'd like to compare here
df = pd.DataFrame(wordtest)
columns = df.columns[1:]
new_df = df.copy(deep=True)
for i in columns:
new_df.iloc[:, i] = df.iloc[:, 0]
new_df
I think this is completely wrong. Could you set the direction?
In the end, I want to count up to the number of correct answers.
python
>>> df = pd.DataFrame({"Answer"):["Next", "From", "Come", "Label", "Button"],
"YOUNGHEE":["Next", "From", "Come", "Label", "Button",
"Chul-soo":["Don't know", "Don't know", "Don't know", "Don't know",
"Kiyoung":["Next", "From", "Come", "Don't Know", "Button"]})
>>> df["Answer"] == df["Kiyoung"]
0 True
1 True
2 True
3 False
4 True
dtype: bool
>>> len (df["Answer"] == df["Kiyoung"])
5
>>> (df["Answer"] == df["Kiyoung"]).sum()
4
>>>
Try scalar, spark
val datas = Map(
"Answer" -> List ("Next", "From", "Come", "Label", "Button")),
"YOUNG HEE" -> List ("Next", "From", "Come", "Label", "Button")),
"Withdrawal" -> List ("I don't know", "I don't know", "I don't know", "I don't know",
"Kiyoung" -> List ("Next", "From", "Come", "Don't Know", "Buttons")
)
val (keys, values) = (datas.keys.toList, datas.values.toList)
val df = (values(0), values(1), values(2), values(3))._1.zip(t._2)
.zip(t._3)
.zip(t._4)
.map {
case (((a, b), c), d) => (a, b, c, d)
}.toDF(keys:_*)
df.agg(
count($"correct" === $"YOUNGHEE", true).as ("YOUNG HEE SCORE"),
count($"correct" === $"withdrawal", true).as ("Withdrawal Score"),
count($"correct" === $"write", true).as ("Starting Score")
).show
+--------+--------+--------+
| Younghee Score | Chulsoo Score | Kiyoung Score |
+--------+--------+--------+
| 5| 0| 4|
+--------+--------+--------+
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